commit 1aa556267e6e1cce909b4efec92ea45d44b6dba5 parent be62c9be841c7959775062946e4d8c7e0a1b89f2 Author: miksa <milutin@popovic.xyz> Date: Mon, 30 Oct 2023 09:28:35 +0000 add pres Diffstat:
| M | nlin_opt/prog/.ipynb_checkpoints/sesh4-checkpoint.ipynb | | | 204 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++---- |
| M | nlin_opt/prog/sesh4.ipynb | | | 240 | ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++--- |
| A | opt_sem/andriushchenko23b.pdf | | | 0 | |
| A | opt_sem/pres/build/pres1.aux | | | 51 | +++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.bbl | | | 66 | ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.bcf | | | 2387 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.blg | | | 15 | +++++++++++++++ |
| A | opt_sem/pres/build/pres1.fdb_latexmk | | | 305 | ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.fls | | | 1789 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.log | | | 1471 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.nav | | | 26 | ++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.out | | | 1 | + |
| A | opt_sem/pres/build/pres1.pdf | | | 0 | |
| A | opt_sem/pres/build/pres1.run.xml | | | 85 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/build/pres1.snm | | | 0 | |
| A | opt_sem/pres/build/pres1.toc | | | 0 | |
| A | opt_sem/pres/pics/resnet18.png | | | 0 | |
| A | opt_sem/pres/pres1.tex | | | 157 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/pres_intro.md | | | 86 | +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ |
| A | opt_sem/pres/uni.bib | | | 8 | ++++++++ |
| A | opt_sem/understanding_machine_learning.pdf | | | 0 |
21 files changed, 6876 insertions(+), 15 deletions(-)
diff --git a/nlin_opt/prog/.ipynb_checkpoints/sesh4-checkpoint.ipynb b/nlin_opt/prog/.ipynb_checkpoints/sesh4-checkpoint.ipynb @@ -10,17 +10,37 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 48, "id": "735f4c05", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import numdifftools as nd\n", - "from matplotlib import pyplot as plt" + "from matplotlib import pyplot as plt\n", + "from time import time" ] }, { + "cell_type": "code", + "execution_count": 50, + "id": "aad6fb45-d213-4edc-acdb-227b1575852e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1698581833.0406172" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { "cell_type": "markdown", "id": "893a5d0d", "metadata": {}, @@ -36,7 +56,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 79, "id": "32db45b8", "metadata": {}, "outputs": [], @@ -60,12 +80,180 @@ " x_k_s.append(x_k)\n", " f_k_s.append(f(x_k))\n", " \n", + " return x_k_s, f_k_s\n", + "\n", + "def sgd(\n", + " a: np.ndarray,\n", + " b: np.ndarray,\n", + " x_0: float,\n", + " sig: float,\n", + " beta: float,\n", + " batches: int\n", + ") -> (list[np.ndarray], list[np.ndarray]) :\n", + "\n", + " x_k: np.ndarray = x_0\n", + " x_k_s: list[np.ndarray] = [np.array(x_k)]\n", + " f_k_s: list[np.ndarray] = [f(x_k, a, b)]\n", + "\n", + " batch: int = 0\n", + " b: int = 0\n", + " dx: float = 1e-3\n", + " while b < batches:\n", + " i: int = np.random.randint(0, len(a))\n", + " d_k: np.ndarray = -( fi(x_k+dx, a[i], b[i]) - fi(x_k-dx, a[i],b[i]) ) / (2*dx)\n", + " \n", + " t_k = 1\n", + " while f(x_k + t_k*d_k) > f(x_k) + sig*t_k * np.dot(-d_k, d_k):\n", + " t_k = t_k * beta\n", + "\n", + " x_k = x_k + t_k * d_k\n", + " x_k_s.append(x_k)\n", + " f_k_s.append(f(x_k, a, b))\n", + "\n", + " batch +=1\n", + " if batch == len(f): \n", + " b += 1\n", + " print(f\"Batch: {b}\")\n", + "\n", + " return x_k_s, f_k_s\n", + "\n", + "def gd(a: np.ndarray,\n", + " b: np.ndarray,\n", + " x_0: float,\n", + " eps: float,\n", + " sig: float,\n", + " beta: float\n", + ") -> (list[np.ndarray], list[np.ndarray]):\n", + " x_k = x_0\n", + " x_k_s = [np.array(x_k)]\n", + " f_k_s = [f(x_k, a, b)]\n", + " dx = 1e-3\n", + " while True:\n", + " d_k = -sum(\n", + " 1/(2*dx) * (fi(x_k + dx, a_i, b_i) - fi(x_k + dx, a_i, b_i))\n", + " for a_i, b_i in zip(a, b)\n", + " )\n", + " if np.linalg.norm(d_k) <= eps:\n", + " break\n", + " \n", + " # Find step size (Arnijno Rule)\n", + " t_k = 1\n", + " while f(x_k + t_k*d_k) > f(x_k) + sig*t_k * np.dot(-d_k, d_k):\n", + " t_k = t_k * beta\n", + " \n", + " x_k = x_k + t_k * d_k\n", + " x_k_s.append(x_k)\n", + " f_k_s.append(f(x_k))\n", + " \n", " return x_k_s, f_k_s" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, + "id": "329bf784-5068-41eb-aa89-c0d428778526", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "7f67d95a-f922-4448-9d92-9d8924e8d717", + "metadata": {}, + "outputs": [], + "source": [ + "def fi(x, a_i, b_i):\n", + " return 1/2*(a_i*x-b_i)**2\n", + "\n", + "def f(x, a, b):\n", + " return sum(fi(x, a_i, b_i) for a_i, b_i in zip(a, b))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b9ddeedc-8677-4e06-a921-3ae16c63f2e2", + "metadata": {}, + "outputs": [], + "source": [ + "a: np.ndarray = np.random.rand(1000)\n", + "b: np.ndarray = np.random.rand(1000)\n", + "x_0: float = 8.0\n", + "sig: float = 10e-2\n", + "beta: float = 1/2\n", + "batches: int = 100\n", + "\n", + "start_gd = time()\n", + "gd_x_s, gd_f_s = gd(a, b, x_0, dx, eps, sig, beta)\n", + "end_gd = time()\n", + "\n", + "start_sgd = time()\n", + "sgd_x_s, sgd_f_s = sgd(a, b, x_0, dx, sig, beta, batches)\n", + "end_sgd = time()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "548b807c-2dd7-45c5-8ebd-f3b22bee7f04", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f17e0674-9cdc-458f-81c6-3fb009cd3c4c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c512cf8-c8d8-46bf-9ce3-6cf4724b522e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "73f81ea4-a5ba-413f-a2f9-f3351aae5612", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7f8badf71ed0>]" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(-10, 10, 1000)\n", + "y = f(x, a, b)\n", + "\n", + "plt.plot(x, np.gradient(y))" + ] + }, + { + "cell_type": "code", + "execution_count": 55, "id": "1566d486", "metadata": {}, "outputs": [ @@ -75,13 +263,13 @@ "Text(0.5, 1.0, '$cos(x)$')" ] }, - "execution_count": 3, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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"text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -265,7 +453,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -279,7 +467,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/nlin_opt/prog/sesh4.ipynb b/nlin_opt/prog/sesh4.ipynb @@ -17,7 +17,8 @@ "source": [ "import numpy as np\n", "import numdifftools as nd\n", - "from matplotlib import pyplot as plt" + "from matplotlib import pyplot as plt\n", + "from time import time" ] }, { @@ -36,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 7, "id": "32db45b8", "metadata": {}, "outputs": [], @@ -60,12 +61,237 @@ " x_k_s.append(x_k)\n", " f_k_s.append(f(x_k))\n", " \n", + " return x_k_s, f_k_s\n", + "\n", + "def sgd(\n", + " a: np.ndarray,\n", + " b: np.ndarray,\n", + " x_0: float,\n", + " step: float,\n", + " sig: float,\n", + " beta: float,\n", + " batches: int\n", + ") -> (list[np.ndarray], list[np.ndarray]) :\n", + "\n", + " x_k: np.ndarray = x_0\n", + " x_k_s: list[np.ndarray] = [np.array(x_k)]\n", + " f_k_s: list[np.ndarray] = [f(x_k, a, b)]\n", + "\n", + " batch: int = 0\n", + " count: int = 0\n", + " dx: float = 1e-3\n", + " while count < batches:\n", + " i = np.random.randint(0, len(a))\n", + " d_k = -( fi(x_k+dx, a[i], b[i]) - fi(x_k-dx, a[i],b[i]) ) / (2*dx)\n", + " \n", + "\n", + " x_k = x_k + step * d_k\n", + " x_k_s.append(x_k)\n", + " f_k_s.append(f(x_k, a, b))\n", + "\n", + " batch +=1\n", + " if batch == len(a): \n", + " count += 1\n", + " batch = 0\n", + " if batch % 10: print(f\"Batch: {count}\")\n", + "\n", + " return x_k_s, f_k_s\n", + "\n", + "def gd(a: np.ndarray,\n", + " b: np.ndarray,\n", + " x_0: float,\n", + " eps: float,\n", + " sig: float,\n", + " beta: float\n", + ") -> (list[np.ndarray], list[np.ndarray]):\n", + " x_k = x_0\n", + " x_k_s = [np.array(x_k)]\n", + " f_k_s = [f(x_k, a, b)]\n", + " dx = 1e-3\n", + " while True:\n", + " d_k = -sum(\n", + " 1/(2*dx) * (fi(x_k + dx, a_i, b_i) - fi(x_k - dx, a_i, b_i))\n", + " for a_i, b_i in zip(a, b)\n", + " )\n", + " if np.linalg.norm(d_k) <= eps:\n", + " break\n", + " \n", + " # Find step size (Arnijno Rule)\n", + " t_k = 1\n", + " while f(x_k + t_k*d_k, a, b) > f(x_k, a, b) + sig*t_k * np.dot(-d_k, d_k):\n", + " t_k = t_k * beta\n", + " \n", + " x_k = x_k + t_k * d_k\n", + " x_k_s.append(x_k)\n", + " f_k_s.append(f(x_k, a, b))\n", + " \n", " return x_k_s, f_k_s" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 8, + "id": "7f67d95a-f922-4448-9d92-9d8924e8d717", + "metadata": {}, + "outputs": [], + "source": [ + "def fi(x, a_i, b_i):\n", + " return 1/2*(a_i*x-b_i)**2\n", + "\n", + "def f(x, a, b):\n", + " return sum(fi(x, a_i, b_i) for a_i, b_i in zip(a, b))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "b9ddeedc-8677-4e06-a921-3ae16c63f2e2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "GD time: 5.241256237030029 solution f=724.5575474470213 x=0.7524298491826923 steps=42\n", + "SGD time: 46.92195749282837 solution: f=724.5969941867688 x=0.757302266459075, steps=10001\n" + ] + } + ], + "source": [ + "a: np.ndarray = np.random.rand(10000)\n", + "b: np.ndarray = np.random.rand(10000)\n", + "x_0: float = 8.0\n", + "sig: float = 10e-2\n", + "beta: float = 1/2\n", + "step: float = 0.01;\n", + "batches: int = 1\n", + "eps: float = 1e-4\n", + "\n", + "start_gd = time()\n", + "gd_x_s, gd_f_s = gd(a, b, x_0, eps, sig, beta)\n", + "end_gd = time()\n", + "print(f\"GD time: {end_gd-start_gd} solution f={gd_f_s[-1]} x={gd_x_s[-1]} steps={len(gd_x_s)}\")\n", + "\n", + "start_sgd = time()\n", + "sgd_x_s, sgd_f_s = sgd(a, b, x_0, step, sig, beta, batches)\n", + "end_sgd = time()\n", + "print(f\"SGD time: {end_sgd-start_sgd} solution: f={sgd_f_s[-1]} x={sgd_x_s[-1]}, steps={len(sgd_x_s)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "3adfe4ea-2a66-4fc6-8dd7-54ed6dbb177a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7f505a197110>]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(gd_f_s, c='r', marker='.')\n", + "plt.plot(sgd_f_s, c='g', marker='.')" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "id": "23efecf0-011a-44ce-b992-225aab3f7fee", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "92.93535542501762" + ] + }, + "execution_count": 149, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0f4ddaa2-41f7-4adc-841d-e578012faac4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 159, + "id": "73f81ea4-a5ba-413f-a2f9-f3351aae5612", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<matplotlib.collections.PathCollection at 0x7f8ba0e57b10>" + ] + }, + "execution_count": 159, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(-2.5, 9, 100)\n", + "y = f(x, a, b)\n", + "\n", + "plt.plot(x, y)\n", + "plt.scatter(sgd_x_s, sgd_f_s, c='r', marker='.', linewidth=0.1)\n", + "plt.scatter(gd_x_s, gd_f_s, c='g', marker='.', linewidth=0.1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bbca4274-0b5e-4cec-8d0a-56adc168ada5", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "87f45449-e772-4fc6-94f1-6137dbff477b", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 55, "id": "1566d486", "metadata": {}, "outputs": [ @@ -75,13 +301,13 @@ "Text(0.5, 1.0, '$cos(x)$')" ] }, - "execution_count": 3, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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"text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -265,7 +491,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -279,7 +505,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.11.5" } }, "nbformat": 4, diff --git a/opt_sem/andriushchenko23b.pdf b/opt_sem/andriushchenko23b.pdf Binary files differ. diff --git a/opt_sem/pres/build/pres1.aux b/opt_sem/pres/build/pres1.aux @@ -0,0 +1,51 @@ +\relax +\providecommand\hyper@newdestlabel[2]{} +\providecommand\HyperFirstAtBeginDocument{\AtBeginDocument} +\HyperFirstAtBeginDocument{\ifx\hyper@anchor\@undefined +\global\let\oldnewlabel\newlabel +\gdef\newlabel#1#2{\newlabelxx{#1}#2} +\gdef\newlabelxx#1#2#3#4#5#6{\oldnewlabel{#1}{{#2}{#3}}} +\AtEndDocument{\ifx\hyper@anchor\@undefined +\let\newlabel\oldnewlabel +\fi} +\fi} +\global\let\hyper@last\relax +\gdef\HyperFirstAtBeginDocument#1{#1} +\providecommand\HyField@AuxAddToFields[1]{} +\providecommand\HyField@AuxAddToCoFields[2]{} +\abx@aux@refcontext{none/global//global/global} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{1}{1/1}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {1}{1}}} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{2}{2/2}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {2}{2}}} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{3}{3/4}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {3}{4}}} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{4}{5/8}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {5}{8}}} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{5}{9/9}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {9}{9}}} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{6}{10/14}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {10}{14}}} +\abx@aux@cite{0}{andriushchenko2023sgd} +\abx@aux@segm{0}{0}{andriushchenko2023sgd} +\abx@aux@cite{0}{andriushchenko2023sgd} +\abx@aux@segm{0}{0}{andriushchenko2023sgd} +\@writefile{nav}{\headcommand {\slideentry {0}{0}{7}{15/16}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {15}{16}}} +\abx@aux@cite{0}{andriushchenko2023sgd} +\abx@aux@segm{0}{0}{andriushchenko2023sgd} +\@writefile{nav}{\headcommand {\beamer@sectionpages {1}{16}}} +\@writefile{nav}{\headcommand {\beamer@subsectionpages {1}{16}}} +\@writefile{nav}{\headcommand {\sectionentry {1}{References}{17}{References}{0}}} +\@writefile{nav}{\headcommand {\slideentry {1}{0}{0}{17/17}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {17}{17}}} +\@writefile{nav}{\headcommand {\beamer@partpages {1}{17}}} +\@writefile{nav}{\headcommand {\beamer@subsectionpages {1}{17}}} +\@writefile{nav}{\headcommand {\beamer@sectionpages {1}{17}}} +\@writefile{nav}{\headcommand {\beamer@documentpages {17}}} +\@writefile{nav}{\headcommand {\gdef \inserttotalframenumber {8}}} +\@writefile{nav}{\headcommand {\slideentry {1}{0}{1}{18/18}{}{0}}} +\@writefile{nav}{\headcommand {\beamer@framepages {18}{18}}} +\abx@aux@read@bbl@mdfivesum{C80A671A95609C193326D73EA38ABCD9} +\abx@aux@defaultrefcontext{0}{andriushchenko2023sgd}{none/global//global/global} +\gdef \@abspage@last{18} diff --git a/opt_sem/pres/build/pres1.bbl b/opt_sem/pres/build/pres1.bbl @@ -0,0 +1,66 @@ +% $ biblatex auxiliary file $ +% $ biblatex bbl format version 3.2 $ +% Do not modify the above lines! +% +% This is an auxiliary file used by the 'biblatex' package. +% This file may safely be deleted. It will be recreated by +% biber as required. +% +\begingroup +\makeatletter +\@ifundefined{ver@biblatex.sty} + {\@latex@error + {Missing 'biblatex' package} + {The bibliography requires the 'biblatex' package.} + \aftergroup\endinput} + {} +\endgroup + + +\refsection{0} + \datalist[entry]{none/global//global/global} + \entry{andriushchenko2023sgd}{misc}{} + \name{author}{4}{}{% + {{hash=37eab590a70071733a7207c69c1de93b}{% + family={Andriushchenko}, + familyi={A\bibinitperiod}, + given={Maksym}, + giveni={M\bibinitperiod}}}% + {{hash=9fc1f76e3c692d87158c46b83e5d28af}{% + family={Varre}, + familyi={V\bibinitperiod}, + given={Aditya}, + giveni={A\bibinitperiod}}}% + {{hash=e7abbaf3659900c715981a63c38087a0}{% + family={Pillaud-Vivien}, + familyi={P\bibinithyphendelim V\bibinitperiod}, + given={Loucas}, + giveni={L\bibinitperiod}}}% + {{hash=e2d7053f85144a452931150e4ba9f19c}{% + family={Flammarion}, + familyi={F\bibinitperiod}, + given={Nicolas}, + giveni={N\bibinitperiod}}}% + } + \strng{namehash}{938351616ba63b95aed77418d24ba110} + \strng{fullhash}{0d250031ed13f608dcd2666e771c5674} + \strng{bibnamehash}{938351616ba63b95aed77418d24ba110} + \strng{authorbibnamehash}{938351616ba63b95aed77418d24ba110} + \strng{authornamehash}{938351616ba63b95aed77418d24ba110} + \strng{authorfullhash}{0d250031ed13f608dcd2666e771c5674} + \field{sortinit}{1} + \field{sortinithash}{4f6aaa89bab872aa0999fec09ff8e98a} + \field{labelnamesource}{author} + \field{labeltitlesource}{title} + \field{eprintclass}{cs.LG} + \field{eprinttype}{arXiv} + \field{title}{SGD with Large Step Sizes Learns Sparse Features} + \field{year}{2023} + \verb{eprint} + \verb 2210.05337 + \endverb + \endentry + \enddatalist +\endrefsection +\endinput + diff --git a/opt_sem/pres/build/pres1.bcf b/opt_sem/pres/build/pres1.bcf @@ -0,0 +1,2387 @@ +<?xml version="1.0" encoding="UTF-8"?> +<bcf:controlfile version="3.10" bltxversion="3.19" xmlns:bcf="https://sourceforge.net/projects/biblatex"> + <!-- BIBER OPTIONS --> + 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<bcf:key>nohashothers</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>noroman</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>nosortothers</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>singletitle</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>skipbib</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>skipbiblist</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>skiplab</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniquelist</bcf:key> + <bcf:value>false</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniquename</bcf:key> + <bcf:value>false</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniqueprimaryauthor</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniquetitle</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniquebaretitle</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>uniquework</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useprefix</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useafterword</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useannotator</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useauthor</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usebookauthor</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usecommentator</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useeditor</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useeditora</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useeditorb</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useeditorc</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useforeword</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useholder</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useintroduction</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usenamea</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usenameb</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usenamec</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>usetranslator</bcf:key> + <bcf:value>0</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useshortauthor</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + <bcf:option type="singlevalued"> + <bcf:key>useshorteditor</bcf:key> + <bcf:value>1</bcf:value> + </bcf:option> + </bcf:options> + <!-- BIBLATEX OPTION SCOPE --> + <bcf:optionscope type="GLOBAL"> + <bcf:option datatype="xml">datamodel</bcf:option> + <bcf:option datatype="xml">labelalphanametemplate</bcf:option> + <bcf:option datatype="xml">labelalphatemplate</bcf:option> + <bcf:option datatype="xml">inheritance</bcf:option> + <bcf:option datatype="xml">translit</bcf:option> + <bcf:option datatype="xml">uniquenametemplate</bcf:option> + <bcf:option datatype="xml">sortingnamekeytemplate</bcf:option> + <bcf:option datatype="xml">sortingtemplate</bcf:option> + <bcf:option datatype="xml">extradatespec</bcf:option> + <bcf:option datatype="xml">extradatecontext</bcf:option> + <bcf:option datatype="xml">labelnamespec</bcf:option> + <bcf:option datatype="xml">labeltitlespec</bcf:option> + <bcf:option datatype="xml">labeldatespec</bcf:option> + <bcf:option datatype="string">controlversion</bcf:option> + <bcf:option datatype="string">alphaothers</bcf:option> + <bcf:option datatype="string">sortalphaothers</bcf:option> + <bcf:option datatype="string">presort</bcf:option> + <bcf:option datatype="string">texencoding</bcf:option> + <bcf:option datatype="string">bibencoding</bcf:option> + <bcf:option datatype="string">sortingtemplatename</bcf:option> + <bcf:option datatype="string">sortlocale</bcf:option> + <bcf:option datatype="string">language</bcf:option> + <bcf:option datatype="string">autolang</bcf:option> + <bcf:option datatype="string">langhook</bcf:option> + <bcf:option datatype="string">indexing</bcf:option> + <bcf:option datatype="string">hyperref</bcf:option> + <bcf:option datatype="string">backrefsetstyle</bcf:option> + <bcf:option datatype="string">block</bcf:option> + <bcf:option datatype="string">pagetracker</bcf:option> + <bcf:option datatype="string">citecounter</bcf:option> + <bcf:option datatype="string">citetracker</bcf:option> + <bcf:option datatype="string">ibidtracker</bcf:option> + <bcf:option datatype="string">idemtracker</bcf:option> + <bcf:option datatype="string">opcittracker</bcf:option> + <bcf:option datatype="string">loccittracker</bcf:option> + <bcf:option datatype="string">labeldate</bcf:option> + <bcf:option datatype="string">labeltime</bcf:option> + <bcf:option datatype="string">dateera</bcf:option> + <bcf:option datatype="string">date</bcf:option> + <bcf:option datatype="string">time</bcf:option> + <bcf:option datatype="string">eventdate</bcf:option> + <bcf:option datatype="string">eventtime</bcf:option> + <bcf:option datatype="string">origdate</bcf:option> + <bcf:option datatype="string">origtime</bcf:option> + <bcf:option datatype="string">urldate</bcf:option> + <bcf:option datatype="string">urltime</bcf:option> + <bcf:option datatype="string">alldatesusetime</bcf:option> + <bcf:option datatype="string">alldates</bcf:option> + <bcf:option datatype="string">alltimes</bcf:option> + <bcf:option datatype="string">gregorianstart</bcf:option> + <bcf:option datatype="string">autocite</bcf:option> + <bcf:option datatype="string">notetype</bcf:option> + <bcf:option datatype="string">uniquelist</bcf:option> + <bcf:option datatype="string">uniquename</bcf:option> + <bcf:option datatype="string">refsection</bcf:option> + <bcf:option datatype="string">refsegment</bcf:option> + <bcf:option datatype="string">citereset</bcf:option> + <bcf:option datatype="string">sortlos</bcf:option> + <bcf:option datatype="string">babel</bcf:option> + <bcf:option datatype="string">datelabel</bcf:option> + <bcf:option datatype="string">backrefstyle</bcf:option> + <bcf:option datatype="string">arxiv</bcf:option> + <bcf:option datatype="boolean">familyinits</bcf:option> + <bcf:option datatype="boolean">giveninits</bcf:option> + <bcf:option datatype="boolean">prefixinits</bcf:option> + <bcf:option datatype="boolean">suffixinits</bcf:option> + <bcf:option datatype="boolean">useafterword</bcf:option> + <bcf:option datatype="boolean">useannotator</bcf:option> + <bcf:option datatype="boolean">useauthor</bcf:option> + <bcf:option datatype="boolean">usebookauthor</bcf:option> + <bcf:option datatype="boolean">usecommentator</bcf:option> + <bcf:option datatype="boolean">useeditor</bcf:option> + <bcf:option datatype="boolean">useeditora</bcf:option> + <bcf:option datatype="boolean">useeditorb</bcf:option> + <bcf:option datatype="boolean">useeditorc</bcf:option> + <bcf:option datatype="boolean">useforeword</bcf:option> + <bcf:option datatype="boolean">useholder</bcf:option> + <bcf:option datatype="boolean">useintroduction</bcf:option> + <bcf:option datatype="boolean">usenamea</bcf:option> + <bcf:option datatype="boolean">usenameb</bcf:option> + <bcf:option datatype="boolean">usenamec</bcf:option> + <bcf:option datatype="boolean">usetranslator</bcf:option> + <bcf:option datatype="boolean">useshortauthor</bcf:option> + <bcf:option datatype="boolean">useshorteditor</bcf:option> + <bcf:option datatype="boolean">debug</bcf:option> + <bcf:option datatype="boolean">loadfiles</bcf:option> + <bcf:option datatype="boolean">safeinputenc</bcf:option> + <bcf:option datatype="boolean">sortcase</bcf:option> + <bcf:option datatype="boolean">sortupper</bcf:option> + <bcf:option datatype="boolean">terseinits</bcf:option> + <bcf:option datatype="boolean">abbreviate</bcf:option> + <bcf:option datatype="boolean">dateabbrev</bcf:option> + <bcf:option datatype="boolean">clearlang</bcf:option> + <bcf:option datatype="boolean">sortcites</bcf:option> + <bcf:option datatype="boolean">sortsets</bcf:option> + <bcf:option datatype="boolean">backref</bcf:option> + <bcf:option datatype="boolean">backreffloats</bcf:option> + <bcf:option datatype="boolean">trackfloats</bcf:option> + <bcf:option datatype="boolean">parentracker</bcf:option> + <bcf:option datatype="boolean">labeldateusetime</bcf:option> + <bcf:option datatype="boolean">datecirca</bcf:option> + <bcf:option datatype="boolean">dateuncertain</bcf:option> + <bcf:option datatype="boolean">dateusetime</bcf:option> + <bcf:option datatype="boolean">eventdateusetime</bcf:option> + <bcf:option datatype="boolean">origdateusetime</bcf:option> + <bcf:option datatype="boolean">urldateusetime</bcf:option> + <bcf:option datatype="boolean">julian</bcf:option> + <bcf:option datatype="boolean">datezeros</bcf:option> + <bcf:option datatype="boolean">timezeros</bcf:option> + <bcf:option datatype="boolean">timezones</bcf:option> + <bcf:option datatype="boolean">seconds</bcf:option> + <bcf:option datatype="boolean">autopunct</bcf:option> + <bcf:option datatype="boolean">punctfont</bcf:option> + <bcf:option datatype="boolean">labelnumber</bcf:option> + <bcf:option datatype="boolean">labelalpha</bcf:option> + <bcf:option datatype="boolean">labeltitle</bcf:option> + <bcf:option datatype="boolean">labeltitleyear</bcf:option> + <bcf:option datatype="boolean">labeldateparts</bcf:option> + <bcf:option datatype="boolean">pluralothers</bcf:option> + <bcf:option datatype="boolean">nohashothers</bcf:option> + <bcf:option datatype="boolean">nosortothers</bcf:option> + <bcf:option datatype="boolean">noroman</bcf:option> + <bcf:option datatype="boolean">singletitle</bcf:option> + <bcf:option datatype="boolean">uniquetitle</bcf:option> + <bcf:option datatype="boolean">uniquebaretitle</bcf:option> + <bcf:option datatype="boolean">uniquework</bcf:option> + <bcf:option datatype="boolean">uniqueprimaryauthor</bcf:option> + <bcf:option datatype="boolean">defernumbers</bcf:option> + <bcf:option datatype="boolean">locallabelwidth</bcf:option> + <bcf:option datatype="boolean">bibwarn</bcf:option> + <bcf:option datatype="boolean">useprefix</bcf:option> + <bcf:option datatype="boolean">skipbib</bcf:option> + <bcf:option datatype="boolean">skipbiblist</bcf:option> + <bcf:option datatype="boolean">skiplab</bcf:option> + <bcf:option datatype="boolean">dataonly</bcf:option> + <bcf:option datatype="boolean">defernums</bcf:option> + <bcf:option datatype="boolean">firstinits</bcf:option> + <bcf:option datatype="boolean">sortfirstinits</bcf:option> + <bcf:option datatype="boolean">sortgiveninits</bcf:option> + <bcf:option datatype="boolean">labelyear</bcf:option> + <bcf:option datatype="boolean">isbn</bcf:option> + <bcf:option datatype="boolean">url</bcf:option> + <bcf:option datatype="boolean">doi</bcf:option> + <bcf:option datatype="boolean">eprint</bcf:option> + <bcf:option datatype="boolean">related</bcf:option> + <bcf:option datatype="boolean">subentry</bcf:option> + <bcf:option datatype="boolean">bibtexcaseprotection</bcf:option> + <bcf:option datatype="integer">mincrossrefs</bcf:option> + <bcf:option datatype="integer">minxrefs</bcf:option> + <bcf:option datatype="integer">maxnames</bcf:option> + <bcf:option datatype="integer">minnames</bcf:option> + <bcf:option datatype="integer">maxbibnames</bcf:option> + <bcf:option datatype="integer">minbibnames</bcf:option> + <bcf:option datatype="integer">maxcitenames</bcf:option> + <bcf:option datatype="integer">mincitenames</bcf:option> + <bcf:option datatype="integer">maxsortnames</bcf:option> + <bcf:option datatype="integer">minsortnames</bcf:option> + <bcf:option datatype="integer">maxitems</bcf:option> + <bcf:option datatype="integer">minitems</bcf:option> + <bcf:option datatype="integer">maxalphanames</bcf:option> + <bcf:option datatype="integer">minalphanames</bcf:option> + <bcf:option datatype="integer">maxparens</bcf:option> + <bcf:option datatype="integer">dateeraauto</bcf:option> + </bcf:optionscope> + <bcf:optionscope type="ENTRYTYPE"> + <bcf:option datatype="string">alphaothers</bcf:option> + <bcf:option datatype="string">sortalphaothers</bcf:option> + <bcf:option datatype="string">presort</bcf:option> + <bcf:option datatype="string">indexing</bcf:option> + <bcf:option datatype="string">citetracker</bcf:option> + <bcf:option datatype="string">ibidtracker</bcf:option> + <bcf:option datatype="string">idemtracker</bcf:option> + <bcf:option datatype="string">opcittracker</bcf:option> + <bcf:option datatype="string">loccittracker</bcf:option> + <bcf:option datatype="string">uniquelist</bcf:option> + <bcf:option datatype="string">uniquename</bcf:option> + <bcf:option datatype="boolean">familyinits</bcf:option> + <bcf:option datatype="boolean">giveninits</bcf:option> + <bcf:option datatype="boolean">prefixinits</bcf:option> + <bcf:option datatype="boolean">suffixinits</bcf:option> + <bcf:option datatype="boolean">useafterword</bcf:option> + <bcf:option datatype="boolean">useannotator</bcf:option> + <bcf:option datatype="boolean">useauthor</bcf:option> + <bcf:option datatype="boolean">usebookauthor</bcf:option> + <bcf:option datatype="boolean">usecommentator</bcf:option> + <bcf:option datatype="boolean">useeditor</bcf:option> + <bcf:option datatype="boolean">useeditora</bcf:option> + <bcf:option datatype="boolean">useeditorb</bcf:option> + <bcf:option datatype="boolean">useeditorc</bcf:option> + <bcf:option datatype="boolean">useforeword</bcf:option> + <bcf:option datatype="boolean">useholder</bcf:option> + <bcf:option datatype="boolean">useintroduction</bcf:option> + <bcf:option datatype="boolean">usenamea</bcf:option> + <bcf:option datatype="boolean">usenameb</bcf:option> + <bcf:option datatype="boolean">usenamec</bcf:option> + <bcf:option datatype="boolean">usetranslator</bcf:option> + <bcf:option datatype="boolean">useshortauthor</bcf:option> + <bcf:option datatype="boolean">useshorteditor</bcf:option> + <bcf:option datatype="boolean">terseinits</bcf:option> + <bcf:option datatype="boolean">abbreviate</bcf:option> + <bcf:option datatype="boolean">dateabbrev</bcf:option> + <bcf:option datatype="boolean">clearlang</bcf:option> + <bcf:option datatype="boolean">labelnumber</bcf:option> + <bcf:option datatype="boolean">labelalpha</bcf:option> + <bcf:option datatype="boolean">labeltitle</bcf:option> + <bcf:option datatype="boolean">labeltitleyear</bcf:option> + <bcf:option datatype="boolean">labeldateparts</bcf:option> + <bcf:option datatype="boolean">nohashothers</bcf:option> + <bcf:option datatype="boolean">nosortothers</bcf:option> + <bcf:option datatype="boolean">noroman</bcf:option> + <bcf:option datatype="boolean">singletitle</bcf:option> + <bcf:option datatype="boolean">uniquetitle</bcf:option> + <bcf:option datatype="boolean">uniquebaretitle</bcf:option> + <bcf:option datatype="boolean">uniquework</bcf:option> + <bcf:option datatype="boolean">uniqueprimaryauthor</bcf:option> + <bcf:option datatype="boolean">useprefix</bcf:option> + <bcf:option datatype="boolean">skipbib</bcf:option> + <bcf:option datatype="boolean">skipbiblist</bcf:option> + <bcf:option datatype="boolean">skiplab</bcf:option> + <bcf:option datatype="boolean">dataonly</bcf:option> + <bcf:option datatype="boolean">skiplos</bcf:option> + <bcf:option datatype="boolean">labelyear</bcf:option> + <bcf:option datatype="boolean">isbn</bcf:option> + <bcf:option datatype="boolean">url</bcf:option> + <bcf:option datatype="boolean">doi</bcf:option> + <bcf:option datatype="boolean">eprint</bcf:option> + <bcf:option datatype="boolean">related</bcf:option> + <bcf:option datatype="boolean">subentry</bcf:option> + <bcf:option datatype="boolean">bibtexcaseprotection</bcf:option> + <bcf:option datatype="xml">labelalphatemplate</bcf:option> + <bcf:option datatype="xml">translit</bcf:option> + <bcf:option datatype="xml">sortexclusion</bcf:option> + <bcf:option datatype="xml">sortinclusion</bcf:option> + <bcf:option datatype="xml">extradatecontext</bcf:option> + <bcf:option datatype="xml">labelnamespec</bcf:option> + <bcf:option datatype="xml">labeltitlespec</bcf:option> + <bcf:option datatype="xml">labeldatespec</bcf:option> + <bcf:option datatype="integer">maxnames</bcf:option> + <bcf:option datatype="integer">minnames</bcf:option> + <bcf:option datatype="integer">maxbibnames</bcf:option> + <bcf:option datatype="integer">minbibnames</bcf:option> + <bcf:option datatype="integer">maxcitenames</bcf:option> + <bcf:option datatype="integer">mincitenames</bcf:option> + <bcf:option datatype="integer">maxsortnames</bcf:option> + <bcf:option datatype="integer">minsortnames</bcf:option> + <bcf:option datatype="integer">maxitems</bcf:option> + <bcf:option datatype="integer">minitems</bcf:option> + <bcf:option datatype="integer">maxalphanames</bcf:option> + <bcf:option datatype="integer">minalphanames</bcf:option> + </bcf:optionscope> + <bcf:optionscope type="ENTRY"> + <bcf:option datatype="string">noinherit</bcf:option> + <bcf:option datatype="string" backendin="sortingnamekeytemplatename,uniquenametemplatename,labelalphanametemplatename">nametemplates</bcf:option> + <bcf:option datatype="string" backendout="1">labelalphanametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">uniquenametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">sortingnamekeytemplatename</bcf:option> + <bcf:option datatype="string">presort</bcf:option> + <bcf:option datatype="string" backendout="1">indexing</bcf:option> + <bcf:option datatype="string" backendout="1">citetracker</bcf:option> + <bcf:option datatype="string" backendout="1">ibidtracker</bcf:option> + <bcf:option datatype="string" backendout="1">idemtracker</bcf:option> + <bcf:option datatype="string" backendout="1">opcittracker</bcf:option> + <bcf:option datatype="string" backendout="1">loccittracker</bcf:option> + <bcf:option datatype="string">uniquelist</bcf:option> + <bcf:option datatype="string">uniquename</bcf:option> + <bcf:option datatype="boolean" backendout="1">familyinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">giveninits</bcf:option> + <bcf:option datatype="boolean" backendout="1">prefixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">suffixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">useafterword</bcf:option> + <bcf:option datatype="boolean" backendout="1">useannotator</bcf:option> + <bcf:option datatype="boolean" backendout="1">useauthor</bcf:option> + <bcf:option datatype="boolean" backendout="1">usebookauthor</bcf:option> + <bcf:option datatype="boolean" backendout="1">usecommentator</bcf:option> + <bcf:option datatype="boolean" backendout="1">useeditor</bcf:option> + <bcf:option datatype="boolean" backendout="1">useeditora</bcf:option> + <bcf:option datatype="boolean" backendout="1">useeditorb</bcf:option> + <bcf:option datatype="boolean" backendout="1">useeditorc</bcf:option> + <bcf:option datatype="boolean" backendout="1">useforeword</bcf:option> + <bcf:option datatype="boolean" backendout="1">useholder</bcf:option> + <bcf:option datatype="boolean" backendout="1">useintroduction</bcf:option> + <bcf:option datatype="boolean" backendout="1">usenamea</bcf:option> + <bcf:option datatype="boolean" backendout="1">usenameb</bcf:option> + <bcf:option datatype="boolean" backendout="1">usenamec</bcf:option> + <bcf:option datatype="boolean" backendout="1">usetranslator</bcf:option> + <bcf:option datatype="boolean" backendout="1">useshortauthor</bcf:option> + <bcf:option datatype="boolean" backendout="1">useshorteditor</bcf:option> + <bcf:option datatype="boolean" backendout="1">terseinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">abbreviate</bcf:option> + <bcf:option datatype="boolean" backendout="1">dateabbrev</bcf:option> + <bcf:option datatype="boolean" backendout="1">clearlang</bcf:option> + <bcf:option datatype="boolean" backendout="1">labelnumber</bcf:option> + <bcf:option datatype="boolean" backendout="1">labelalpha</bcf:option> + <bcf:option datatype="boolean" backendout="1">labeltitle</bcf:option> + <bcf:option datatype="boolean" backendout="1">labeltitleyear</bcf:option> + <bcf:option datatype="boolean" backendout="1">labeldateparts</bcf:option> + <bcf:option datatype="boolean">nohashothers</bcf:option> + <bcf:option datatype="boolean">nosortothers</bcf:option> + <bcf:option datatype="boolean">noroman</bcf:option> + <bcf:option datatype="boolean">singletitle</bcf:option> + <bcf:option datatype="boolean">uniquetitle</bcf:option> + <bcf:option datatype="boolean">uniquebaretitle</bcf:option> + <bcf:option datatype="boolean">uniquework</bcf:option> + <bcf:option datatype="boolean">uniqueprimaryauthor</bcf:option> + <bcf:option datatype="boolean" backendout="1">useprefix</bcf:option> + <bcf:option datatype="boolean" backendout="1">skipbib</bcf:option> + <bcf:option datatype="boolean" backendout="1">skipbiblist</bcf:option> + <bcf:option datatype="boolean" backendout="1">skiplab</bcf:option> + <bcf:option datatype="boolean" backendin="uniquename=false,uniquelist=false,skipbib=true,skipbiblist=true,skiplab=true">dataonly</bcf:option> + <bcf:option datatype="boolean" backendout="1">skiplos</bcf:option> + <bcf:option datatype="boolean" backendout="1">isbn</bcf:option> + <bcf:option datatype="boolean" backendout="1">url</bcf:option> + <bcf:option datatype="boolean" backendout="1">doi</bcf:option> + <bcf:option datatype="boolean" backendout="1">eprint</bcf:option> + <bcf:option datatype="boolean" backendout="1">related</bcf:option> + <bcf:option datatype="boolean" backendout="1">subentry</bcf:option> + <bcf:option datatype="boolean" backendout="1">bibtexcaseprotection</bcf:option> + <bcf:option datatype="integer" backendin="maxcitenames,maxbibnames,maxsortnames">maxnames</bcf:option> + <bcf:option datatype="integer" backendin="mincitenames,minbibnames,minsortnames">minnames</bcf:option> + <bcf:option datatype="integer" backendout="1">maxbibnames</bcf:option> + <bcf:option datatype="integer" backendout="1">minbibnames</bcf:option> + <bcf:option datatype="integer" backendout="1">maxcitenames</bcf:option> + <bcf:option datatype="integer" backendout="1">mincitenames</bcf:option> + <bcf:option datatype="integer" backendout="1">maxsortnames</bcf:option> + <bcf:option datatype="integer" backendout="1">minsortnames</bcf:option> + <bcf:option datatype="integer" backendout="1">maxitems</bcf:option> + <bcf:option datatype="integer" backendout="1">minitems</bcf:option> + <bcf:option datatype="integer" backendout="1">maxalphanames</bcf:option> + <bcf:option datatype="integer" backendout="1">minalphanames</bcf:option> + </bcf:optionscope> + <bcf:optionscope type="NAMELIST"> + <bcf:option datatype="string" backendin="sortingnamekeytemplatename,uniquenametemplatename,labelalphanametemplatename">nametemplates</bcf:option> + <bcf:option datatype="string" backendout="1">labelalphanametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">uniquenametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">sortingnamekeytemplatename</bcf:option> + <bcf:option datatype="string">uniquelist</bcf:option> + <bcf:option datatype="string">uniquename</bcf:option> + <bcf:option datatype="boolean" backendout="1">familyinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">giveninits</bcf:option> + <bcf:option datatype="boolean" backendout="1">prefixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">suffixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">terseinits</bcf:option> + <bcf:option datatype="boolean">nohashothers</bcf:option> + <bcf:option datatype="boolean">nosortothers</bcf:option> + <bcf:option datatype="boolean" backendout="1">useprefix</bcf:option> + </bcf:optionscope> + <bcf:optionscope type="NAME"> + <bcf:option datatype="string" backendin="sortingnamekeytemplatename,uniquenametemplatename,labelalphanametemplatename">nametemplates</bcf:option> + <bcf:option datatype="string" backendout="1">labelalphanametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">uniquenametemplatename</bcf:option> + <bcf:option datatype="string" backendout="1">sortingnamekeytemplatename</bcf:option> + <bcf:option datatype="string">uniquename</bcf:option> + <bcf:option datatype="boolean" backendout="1">familyinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">giveninits</bcf:option> + <bcf:option datatype="boolean" backendout="1">prefixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">suffixinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">terseinits</bcf:option> + <bcf:option datatype="boolean" backendout="1">useprefix</bcf:option> + </bcf:optionscope> + <!-- DATAFIELDSETS --> + <bcf:datafieldset name="setnames"> + <bcf:member datatype="name" fieldtype="list"/> + </bcf:datafieldset> + <bcf:datafieldset name="settitles"> + <bcf:member field="title"/> + <bcf:member field="booktitle"/> + <bcf:member field="eventtitle"/> + <bcf:member field="issuetitle"/> + <bcf:member field="journaltitle"/> + <bcf:member field="maintitle"/> + <bcf:member field="origtitle"/> + </bcf:datafieldset> + <!-- SOURCEMAP --> + <bcf:sourcemap> + <bcf:maps datatype="bibtex" level="driver"> + <bcf:map> + <bcf:map_step map_field_set="day" map_null="1"/> + </bcf:map> + <bcf:map> + <bcf:map_step map_type_source="conference" map_type_target="inproceedings"/> + <bcf:map_step map_type_source="electronic" map_type_target="online"/> + <bcf:map_step map_type_source="www" map_type_target="online"/> + </bcf:map> + <bcf:map> + <bcf:map_step map_type_source="mastersthesis" map_type_target="thesis" map_final="1"/> + <bcf:map_step map_field_set="type" map_field_value="mathesis"/> + </bcf:map> + <bcf:map> + <bcf:map_step map_type_source="phdthesis" map_type_target="thesis" map_final="1"/> + <bcf:map_step map_field_set="type" map_field_value="phdthesis"/> + </bcf:map> + <bcf:map> + <bcf:map_step map_type_source="techreport" map_type_target="report" map_final="1"/> + <bcf:map_step map_field_set="type" map_field_value="techreport"/> + </bcf:map> + <bcf:map> + <bcf:map_step map_field_source="hyphenation" map_field_target="langid"/> + <bcf:map_step map_field_source="address" map_field_target="location"/> + <bcf:map_step map_field_source="school" map_field_target="institution"/> + <bcf:map_step map_field_source="annote" map_field_target="annotation"/> + <bcf:map_step map_field_source="archiveprefix" map_field_target="eprinttype"/> + <bcf:map_step map_field_source="journal" map_field_target="journaltitle"/> + <bcf:map_step map_field_source="primaryclass" map_field_target="eprintclass"/> + <bcf:map_step map_field_source="key" map_field_target="sortkey"/> + <bcf:map_step map_field_source="pdf" map_field_target="file"/> + </bcf:map> + </bcf:maps> + </bcf:sourcemap> + <!-- LABELALPHA NAME TEMPLATE --> + <bcf:labelalphanametemplate name="global"> + <bcf:namepart order="1" use="1" pre="1" substring_width="1" substring_compound="1">prefix</bcf:namepart> + <bcf:namepart order="2">family</bcf:namepart> + </bcf:labelalphanametemplate> + <!-- LABELALPHA TEMPLATE --> + <bcf:labelalphatemplate type="global"> + <bcf:labelelement order="1"> + <bcf:labelpart final="1">shorthand</bcf:labelpart> + <bcf:labelpart>label</bcf:labelpart> + <bcf:labelpart substring_width="3" substring_side="left" ifnames="1">labelname</bcf:labelpart> + <bcf:labelpart substring_width="1" substring_side="left">labelname</bcf:labelpart> + </bcf:labelelement> + <bcf:labelelement order="2"> + <bcf:labelpart substring_width="2" substring_side="right">year</bcf:labelpart> + </bcf:labelelement> + </bcf:labelalphatemplate> + <!-- EXTRADATE --> + <bcf:extradatespec> + <bcf:scope> + <bcf:field order="1">labelyear</bcf:field> + <bcf:field order="2">year</bcf:field> + </bcf:scope> + </bcf:extradatespec> + <!-- INHERITANCE --> + <bcf:inheritance> + <bcf:defaults inherit_all="true" override_target="false"> + </bcf:defaults> + <bcf:inherit> + <bcf:type_pair source="mvbook" target="inbook"/> + <bcf:type_pair source="mvbook" target="bookinbook"/> + <bcf:type_pair source="mvbook" target="suppbook"/> + <bcf:type_pair source="book" target="inbook"/> + <bcf:type_pair source="book" target="bookinbook"/> + <bcf:type_pair source="book" target="suppbook"/> + <bcf:field source="author" target="author"/> + <bcf:field source="author" target="bookauthor"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="mvbook" target="book"/> + <bcf:type_pair source="mvbook" target="inbook"/> + <bcf:type_pair source="mvbook" target="bookinbook"/> + <bcf:type_pair source="mvbook" target="suppbook"/> + <bcf:field source="title" target="maintitle"/> + <bcf:field source="subtitle" target="mainsubtitle"/> + <bcf:field source="titleaddon" target="maintitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="mvcollection" target="collection"/> + <bcf:type_pair source="mvcollection" target="reference"/> + <bcf:type_pair source="mvcollection" target="incollection"/> + <bcf:type_pair source="mvcollection" target="inreference"/> + <bcf:type_pair source="mvcollection" target="suppcollection"/> + <bcf:type_pair source="mvreference" target="collection"/> + <bcf:type_pair source="mvreference" target="reference"/> + <bcf:type_pair source="mvreference" target="incollection"/> + <bcf:type_pair source="mvreference" target="inreference"/> + <bcf:type_pair source="mvreference" target="suppcollection"/> + <bcf:field source="title" target="maintitle"/> + <bcf:field source="subtitle" target="mainsubtitle"/> + <bcf:field source="titleaddon" target="maintitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="mvproceedings" target="proceedings"/> + <bcf:type_pair source="mvproceedings" target="inproceedings"/> + <bcf:field source="title" target="maintitle"/> + <bcf:field source="subtitle" target="mainsubtitle"/> + <bcf:field source="titleaddon" target="maintitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="book" target="inbook"/> + <bcf:type_pair source="book" target="bookinbook"/> + <bcf:type_pair source="book" target="suppbook"/> + <bcf:field source="title" target="booktitle"/> + <bcf:field source="subtitle" target="booksubtitle"/> + <bcf:field source="titleaddon" target="booktitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="collection" target="incollection"/> + <bcf:type_pair source="collection" target="inreference"/> + <bcf:type_pair source="collection" target="suppcollection"/> + <bcf:type_pair source="reference" target="incollection"/> + <bcf:type_pair source="reference" target="inreference"/> + <bcf:type_pair source="reference" target="suppcollection"/> + <bcf:field source="title" target="booktitle"/> + <bcf:field source="subtitle" target="booksubtitle"/> + <bcf:field source="titleaddon" target="booktitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="proceedings" target="inproceedings"/> + <bcf:field source="title" target="booktitle"/> + <bcf:field source="subtitle" target="booksubtitle"/> + <bcf:field source="titleaddon" target="booktitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="periodical" target="article"/> + <bcf:type_pair source="periodical" target="suppperiodical"/> + <bcf:field source="title" target="journaltitle"/> + <bcf:field source="subtitle" target="journalsubtitle"/> + <bcf:field source="titleaddon" target="journaltitleaddon"/> + <bcf:field source="shorttitle" skip="true"/> + <bcf:field source="sorttitle" skip="true"/> + <bcf:field source="indextitle" skip="true"/> + <bcf:field source="indexsorttitle" skip="true"/> + </bcf:inherit> + <bcf:inherit> + <bcf:type_pair source="*" target="*"/> + <bcf:field source="ids" skip="true"/> + <bcf:field source="crossref" skip="true"/> + <bcf:field source="xref" skip="true"/> + <bcf:field source="entryset" skip="true"/> + <bcf:field source="entrysubtype" skip="true"/> + <bcf:field source="execute" skip="true"/> + <bcf:field source="label" skip="true"/> + <bcf:field source="options" skip="true"/> + <bcf:field source="presort" skip="true"/> + <bcf:field source="related" skip="true"/> + <bcf:field source="relatedoptions" skip="true"/> + <bcf:field source="relatedstring" skip="true"/> + <bcf:field source="relatedtype" skip="true"/> + <bcf:field source="shorthand" skip="true"/> + <bcf:field source="shorthandintro" skip="true"/> + <bcf:field source="sortkey" skip="true"/> + </bcf:inherit> + </bcf:inheritance> + <!-- UNIQUENAME TEMPLATES --> + <bcf:uniquenametemplate name="global"> + <bcf:namepart order="1" use="1" base="1">prefix</bcf:namepart> + <bcf:namepart order="2" base="1">family</bcf:namepart> + <bcf:namepart order="3">given</bcf:namepart> + </bcf:uniquenametemplate> + <!-- SORTING NAME KEY TEMPLATES --> + <bcf:sortingnamekeytemplate name="global" visibility="sort"> + <bcf:keypart order="1"> + <bcf:part type="namepart" order="1" use="1">prefix</bcf:part> + <bcf:part type="namepart" order="2">family</bcf:part> + </bcf:keypart> + <bcf:keypart order="2"> + <bcf:part type="namepart" order="1">given</bcf:part> + </bcf:keypart> + <bcf:keypart order="3"> + <bcf:part type="namepart" order="1">suffix</bcf:part> + </bcf:keypart> + <bcf:keypart order="4"> + <bcf:part type="namepart" order="1" use="0">prefix</bcf:part> + </bcf:keypart> + </bcf:sortingnamekeytemplate> + <bcf:presort>mm</bcf:presort> + <!-- DATA MODEL --> + <bcf:datamodel> + <bcf:constants> + <bcf:constant type="list" name="gender">sf,sm,sn,pf,pm,pn,pp</bcf:constant> + <bcf:constant type="list" name="nameparts">family,given,prefix,suffix</bcf:constant> + <bcf:constant type="list" name="optiondatatypes">boolean,integer,string,xml</bcf:constant> + <bcf:constant type="list" name="multiscriptforms">default,transliteration,transcription,translation</bcf:constant> + </bcf:constants> + <bcf:entrytypes> + <bcf:entrytype>article</bcf:entrytype> + <bcf:entrytype>artwork</bcf:entrytype> + <bcf:entrytype>audio</bcf:entrytype> + <bcf:entrytype>bibnote</bcf:entrytype> + <bcf:entrytype>book</bcf:entrytype> + <bcf:entrytype>bookinbook</bcf:entrytype> + <bcf:entrytype>booklet</bcf:entrytype> + <bcf:entrytype>collection</bcf:entrytype> + <bcf:entrytype>commentary</bcf:entrytype> + <bcf:entrytype>customa</bcf:entrytype> + <bcf:entrytype>customb</bcf:entrytype> + <bcf:entrytype>customc</bcf:entrytype> + <bcf:entrytype>customd</bcf:entrytype> + <bcf:entrytype>custome</bcf:entrytype> + <bcf:entrytype>customf</bcf:entrytype> + <bcf:entrytype>dataset</bcf:entrytype> + <bcf:entrytype>inbook</bcf:entrytype> + <bcf:entrytype>incollection</bcf:entrytype> + <bcf:entrytype>inproceedings</bcf:entrytype> + <bcf:entrytype>inreference</bcf:entrytype> + <bcf:entrytype>image</bcf:entrytype> + <bcf:entrytype>jurisdiction</bcf:entrytype> + <bcf:entrytype>legal</bcf:entrytype> + <bcf:entrytype>legislation</bcf:entrytype> + <bcf:entrytype>letter</bcf:entrytype> + <bcf:entrytype>manual</bcf:entrytype> + <bcf:entrytype>misc</bcf:entrytype> + <bcf:entrytype>movie</bcf:entrytype> + <bcf:entrytype>music</bcf:entrytype> + <bcf:entrytype>mvcollection</bcf:entrytype> + <bcf:entrytype>mvreference</bcf:entrytype> + <bcf:entrytype>mvproceedings</bcf:entrytype> + <bcf:entrytype>mvbook</bcf:entrytype> + <bcf:entrytype>online</bcf:entrytype> + <bcf:entrytype>patent</bcf:entrytype> + <bcf:entrytype>performance</bcf:entrytype> + <bcf:entrytype>periodical</bcf:entrytype> + <bcf:entrytype>proceedings</bcf:entrytype> + <bcf:entrytype>reference</bcf:entrytype> + <bcf:entrytype>report</bcf:entrytype> + <bcf:entrytype>review</bcf:entrytype> + <bcf:entrytype>set</bcf:entrytype> + <bcf:entrytype>software</bcf:entrytype> + <bcf:entrytype>standard</bcf:entrytype> + <bcf:entrytype>suppbook</bcf:entrytype> + <bcf:entrytype>suppcollection</bcf:entrytype> + <bcf:entrytype>suppperiodical</bcf:entrytype> + <bcf:entrytype>thesis</bcf:entrytype> + <bcf:entrytype>unpublished</bcf:entrytype> + <bcf:entrytype>video</bcf:entrytype> + <bcf:entrytype skip_output="true">xdata</bcf:entrytype> + </bcf:entrytypes> + <bcf:fields> + <bcf:field fieldtype="field" datatype="integer">sortyear</bcf:field> + <bcf:field fieldtype="field" datatype="integer">volume</bcf:field> + <bcf:field fieldtype="field" datatype="integer">volumes</bcf:field> + <bcf:field fieldtype="field" datatype="literal">abstract</bcf:field> + <bcf:field fieldtype="field" datatype="literal">addendum</bcf:field> + <bcf:field fieldtype="field" datatype="literal">annotation</bcf:field> + <bcf:field fieldtype="field" datatype="literal">booksubtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">booktitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">booktitleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">chapter</bcf:field> + <bcf:field fieldtype="field" datatype="literal">edition</bcf:field> + <bcf:field fieldtype="field" datatype="literal">eid</bcf:field> + <bcf:field fieldtype="field" datatype="literal">entrysubtype</bcf:field> + <bcf:field fieldtype="field" datatype="literal">eprintclass</bcf:field> + <bcf:field fieldtype="field" datatype="literal">eprinttype</bcf:field> + <bcf:field fieldtype="field" datatype="literal">eventtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">eventtitleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">gender</bcf:field> + <bcf:field fieldtype="field" datatype="literal">howpublished</bcf:field> + <bcf:field fieldtype="field" datatype="literal">indexsorttitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">indextitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">isan</bcf:field> + <bcf:field fieldtype="field" datatype="literal">isbn</bcf:field> + <bcf:field fieldtype="field" datatype="literal">ismn</bcf:field> + <bcf:field fieldtype="field" datatype="literal">isrn</bcf:field> + <bcf:field fieldtype="field" datatype="literal">issn</bcf:field> + <bcf:field fieldtype="field" datatype="literal">issue</bcf:field> + <bcf:field fieldtype="field" datatype="literal">issuesubtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">issuetitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">issuetitleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">iswc</bcf:field> + <bcf:field fieldtype="field" datatype="literal">journalsubtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">journaltitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">journaltitleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">label</bcf:field> + <bcf:field fieldtype="field" datatype="literal">langid</bcf:field> + <bcf:field fieldtype="field" datatype="literal">langidopts</bcf:field> + <bcf:field fieldtype="field" datatype="literal">library</bcf:field> + <bcf:field fieldtype="field" datatype="literal">mainsubtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">maintitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">maintitleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">nameaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">note</bcf:field> + <bcf:field fieldtype="field" datatype="literal">number</bcf:field> + <bcf:field fieldtype="field" datatype="literal">origtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">pagetotal</bcf:field> + <bcf:field fieldtype="field" datatype="literal">part</bcf:field> + <bcf:field fieldtype="field" datatype="literal">relatedstring</bcf:field> + <bcf:field fieldtype="field" datatype="literal">relatedtype</bcf:field> + <bcf:field fieldtype="field" datatype="literal">reprinttitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">series</bcf:field> + <bcf:field fieldtype="field" datatype="literal">shorthandintro</bcf:field> + <bcf:field fieldtype="field" datatype="literal">subtitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal">title</bcf:field> + <bcf:field fieldtype="field" datatype="literal">titleaddon</bcf:field> + <bcf:field fieldtype="field" datatype="literal">usera</bcf:field> + <bcf:field fieldtype="field" datatype="literal">userb</bcf:field> + <bcf:field fieldtype="field" datatype="literal">userc</bcf:field> + <bcf:field fieldtype="field" datatype="literal">userd</bcf:field> + <bcf:field fieldtype="field" datatype="literal">usere</bcf:field> + <bcf:field fieldtype="field" datatype="literal">userf</bcf:field> + <bcf:field fieldtype="field" datatype="literal">venue</bcf:field> + <bcf:field fieldtype="field" datatype="literal">version</bcf:field> + <bcf:field fieldtype="field" datatype="literal" label="true">shorthand</bcf:field> + <bcf:field fieldtype="field" datatype="literal" label="true">shortjournal</bcf:field> + <bcf:field fieldtype="field" datatype="literal" label="true">shortseries</bcf:field> + <bcf:field fieldtype="field" datatype="literal" label="true">shorttitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal" skip_output="true">sorttitle</bcf:field> + <bcf:field fieldtype="field" datatype="literal" skip_output="true">sortshorthand</bcf:field> + <bcf:field fieldtype="field" datatype="literal" skip_output="true">sortkey</bcf:field> + <bcf:field fieldtype="field" datatype="literal" skip_output="true">presort</bcf:field> + <bcf:field fieldtype="list" datatype="literal">institution</bcf:field> + <bcf:field fieldtype="list" datatype="literal">lista</bcf:field> + <bcf:field fieldtype="list" datatype="literal">listb</bcf:field> + <bcf:field fieldtype="list" datatype="literal">listc</bcf:field> + <bcf:field fieldtype="list" datatype="literal">listd</bcf:field> + <bcf:field fieldtype="list" datatype="literal">liste</bcf:field> + <bcf:field fieldtype="list" datatype="literal">listf</bcf:field> + <bcf:field fieldtype="list" datatype="literal">location</bcf:field> + <bcf:field fieldtype="list" datatype="literal">organization</bcf:field> + <bcf:field fieldtype="list" datatype="literal">origlocation</bcf:field> + <bcf:field fieldtype="list" datatype="literal">origpublisher</bcf:field> + <bcf:field fieldtype="list" datatype="literal">publisher</bcf:field> + <bcf:field fieldtype="list" datatype="name">afterword</bcf:field> + <bcf:field fieldtype="list" datatype="name">annotator</bcf:field> + <bcf:field fieldtype="list" datatype="name">author</bcf:field> + <bcf:field fieldtype="list" datatype="name">bookauthor</bcf:field> + <bcf:field fieldtype="list" datatype="name">commentator</bcf:field> + <bcf:field fieldtype="list" datatype="name">editor</bcf:field> + <bcf:field fieldtype="list" datatype="name">editora</bcf:field> + <bcf:field fieldtype="list" datatype="name">editorb</bcf:field> + <bcf:field fieldtype="list" datatype="name">editorc</bcf:field> + <bcf:field fieldtype="list" datatype="name">foreword</bcf:field> + <bcf:field fieldtype="list" datatype="name">holder</bcf:field> + <bcf:field fieldtype="list" datatype="name">introduction</bcf:field> + <bcf:field fieldtype="list" datatype="name">namea</bcf:field> + <bcf:field fieldtype="list" datatype="name">nameb</bcf:field> + <bcf:field fieldtype="list" datatype="name">namec</bcf:field> + <bcf:field fieldtype="list" datatype="name">translator</bcf:field> + <bcf:field fieldtype="list" datatype="name" label="true">shortauthor</bcf:field> + <bcf:field fieldtype="list" datatype="name" label="true">shorteditor</bcf:field> + <bcf:field fieldtype="list" datatype="name" skip_output="true">sortname</bcf:field> + <bcf:field fieldtype="field" datatype="key">authortype</bcf:field> + <bcf:field fieldtype="field" datatype="key">editoratype</bcf:field> + <bcf:field fieldtype="field" datatype="key">editorbtype</bcf:field> + <bcf:field fieldtype="field" datatype="key">editorctype</bcf:field> + <bcf:field fieldtype="field" datatype="key">editortype</bcf:field> + <bcf:field fieldtype="field" datatype="key">bookpagination</bcf:field> + <bcf:field fieldtype="field" datatype="key">nameatype</bcf:field> + <bcf:field fieldtype="field" datatype="key">namebtype</bcf:field> + <bcf:field fieldtype="field" datatype="key">namectype</bcf:field> + <bcf:field fieldtype="field" datatype="key">pagination</bcf:field> + <bcf:field fieldtype="field" datatype="key">pubstate</bcf:field> + <bcf:field fieldtype="field" datatype="key">type</bcf:field> + <bcf:field fieldtype="list" datatype="key">language</bcf:field> + <bcf:field fieldtype="list" datatype="key">origlanguage</bcf:field> + <bcf:field fieldtype="field" datatype="entrykey">crossref</bcf:field> + <bcf:field fieldtype="field" datatype="entrykey">xref</bcf:field> + <bcf:field fieldtype="field" datatype="date" skip_output="true">date</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">endyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">year</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">month</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">day</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">hour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">minute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">second</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">timezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">yeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">endyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="date" skip_output="true">eventdate</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">eventendyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">eventyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">eventendyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="date" skip_output="true">origdate</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">origendyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">origyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">orighour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">origendyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="date" skip_output="true">urldate</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">urlendyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart" nullok="true">urlyear</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urltimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendmonth</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendday</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendhour</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendminute</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendsecond</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendtimezone</bcf:field> + <bcf:field fieldtype="field" datatype="datepart">urlendyeardivision</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">doi</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">eprint</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">file</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">verba</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">verbb</bcf:field> + <bcf:field fieldtype="field" datatype="verbatim">verbc</bcf:field> + <bcf:field fieldtype="field" datatype="uri">url</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="entrykey" skip_output="true">xdata</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="entrykey" skip_output="true">ids</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="entrykey" skip_output="true">entryset</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="entrykey">related</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="keyword">keywords</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="option" skip_output="true">options</bcf:field> + <bcf:field fieldtype="field" format="xsv" datatype="option" skip_output="true">relatedoptions</bcf:field> + <bcf:field fieldtype="field" datatype="range">pages</bcf:field> + <bcf:field fieldtype="field" datatype="code">execute</bcf:field> + </bcf:fields> + <bcf:entryfields> + <bcf:field>abstract</bcf:field> + <bcf:field>annotation</bcf:field> + <bcf:field>authortype</bcf:field> + <bcf:field>bookpagination</bcf:field> + <bcf:field>crossref</bcf:field> + <bcf:field>day</bcf:field> + <bcf:field>doi</bcf:field> + <bcf:field>eprint</bcf:field> + <bcf:field>eprintclass</bcf:field> + <bcf:field>eprinttype</bcf:field> + <bcf:field>endday</bcf:field> + <bcf:field>endhour</bcf:field> + <bcf:field>endminute</bcf:field> + <bcf:field>endmonth</bcf:field> + <bcf:field>endsecond</bcf:field> + <bcf:field>endtimezone</bcf:field> + <bcf:field>endyear</bcf:field> + <bcf:field>endyeardivision</bcf:field> + <bcf:field>entryset</bcf:field> + <bcf:field>entrysubtype</bcf:field> + <bcf:field>execute</bcf:field> + <bcf:field>file</bcf:field> + <bcf:field>gender</bcf:field> + <bcf:field>hour</bcf:field> + <bcf:field>ids</bcf:field> + <bcf:field>indextitle</bcf:field> + <bcf:field>indexsorttitle</bcf:field> + <bcf:field>isan</bcf:field> + <bcf:field>ismn</bcf:field> + <bcf:field>iswc</bcf:field> + <bcf:field>keywords</bcf:field> + <bcf:field>label</bcf:field> + <bcf:field>langid</bcf:field> + <bcf:field>langidopts</bcf:field> + <bcf:field>library</bcf:field> + <bcf:field>lista</bcf:field> + <bcf:field>listb</bcf:field> + <bcf:field>listc</bcf:field> + <bcf:field>listd</bcf:field> + <bcf:field>liste</bcf:field> + <bcf:field>listf</bcf:field> + <bcf:field>minute</bcf:field> + <bcf:field>month</bcf:field> + <bcf:field>namea</bcf:field> + <bcf:field>nameb</bcf:field> + <bcf:field>namec</bcf:field> + <bcf:field>nameatype</bcf:field> + <bcf:field>namebtype</bcf:field> + <bcf:field>namectype</bcf:field> + <bcf:field>nameaddon</bcf:field> + <bcf:field>options</bcf:field> + <bcf:field>origday</bcf:field> + <bcf:field>origendday</bcf:field> + <bcf:field>origendhour</bcf:field> + <bcf:field>origendminute</bcf:field> + <bcf:field>origendmonth</bcf:field> + <bcf:field>origendsecond</bcf:field> + <bcf:field>origendtimezone</bcf:field> + <bcf:field>origendyear</bcf:field> + <bcf:field>origendyeardivision</bcf:field> + <bcf:field>orighour</bcf:field> + <bcf:field>origminute</bcf:field> + <bcf:field>origmonth</bcf:field> + <bcf:field>origsecond</bcf:field> + <bcf:field>origtimezone</bcf:field> + <bcf:field>origyear</bcf:field> + <bcf:field>origyeardivision</bcf:field> + <bcf:field>origlocation</bcf:field> + <bcf:field>origpublisher</bcf:field> + <bcf:field>origtitle</bcf:field> + <bcf:field>pagination</bcf:field> + <bcf:field>presort</bcf:field> + <bcf:field>related</bcf:field> + <bcf:field>relatedoptions</bcf:field> + <bcf:field>relatedstring</bcf:field> + <bcf:field>relatedtype</bcf:field> + <bcf:field>second</bcf:field> + <bcf:field>shortauthor</bcf:field> + <bcf:field>shorteditor</bcf:field> + <bcf:field>shorthand</bcf:field> + <bcf:field>shorthandintro</bcf:field> + <bcf:field>shortjournal</bcf:field> + <bcf:field>shortseries</bcf:field> + <bcf:field>shorttitle</bcf:field> + <bcf:field>sortkey</bcf:field> + <bcf:field>sortname</bcf:field> + <bcf:field>sortshorthand</bcf:field> + <bcf:field>sorttitle</bcf:field> + <bcf:field>sortyear</bcf:field> + <bcf:field>timezone</bcf:field> + <bcf:field>url</bcf:field> + <bcf:field>urlday</bcf:field> + <bcf:field>urlendday</bcf:field> + <bcf:field>urlendhour</bcf:field> + <bcf:field>urlendminute</bcf:field> + <bcf:field>urlendmonth</bcf:field> + <bcf:field>urlendsecond</bcf:field> + <bcf:field>urlendtimezone</bcf:field> + <bcf:field>urlendyear</bcf:field> + <bcf:field>urlhour</bcf:field> + <bcf:field>urlminute</bcf:field> + <bcf:field>urlmonth</bcf:field> + <bcf:field>urlsecond</bcf:field> + <bcf:field>urltimezone</bcf:field> + <bcf:field>urlyear</bcf:field> + <bcf:field>usera</bcf:field> + <bcf:field>userb</bcf:field> + <bcf:field>userc</bcf:field> + <bcf:field>userd</bcf:field> + <bcf:field>usere</bcf:field> + <bcf:field>userf</bcf:field> + <bcf:field>verba</bcf:field> + <bcf:field>verbb</bcf:field> + <bcf:field>verbc</bcf:field> + <bcf:field>xdata</bcf:field> + <bcf:field>xref</bcf:field> + <bcf:field>year</bcf:field> + <bcf:field>yeardivision</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>set</bcf:entrytype> + <bcf:field>entryset</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>article</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>issn</bcf:field> + <bcf:field>issue</bcf:field> + <bcf:field>issuetitle</bcf:field> + <bcf:field>issuesubtitle</bcf:field> + <bcf:field>issuetitleaddon</bcf:field> + <bcf:field>journalsubtitle</bcf:field> + <bcf:field>journaltitle</bcf:field> + <bcf:field>journaltitleaddon</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>version</bcf:field> + <bcf:field>volume</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>bibnote</bcf:entrytype> + <bcf:field>note</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>book</bcf:entrytype> + <bcf:field>author</bcf:field> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>mvbook</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>inbook</bcf:entrytype> + <bcf:entrytype>bookinbook</bcf:entrytype> + <bcf:entrytype>suppbook</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>booktitle</bcf:field> + <bcf:field>bookauthor</bcf:field> + <bcf:field>booksubtitle</bcf:field> + <bcf:field>booktitleaddon</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>booklet</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>howpublished</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>collection</bcf:entrytype> + <bcf:entrytype>reference</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>mvcollection</bcf:entrytype> + <bcf:entrytype>mvreference</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>incollection</bcf:entrytype> + <bcf:entrytype>suppcollection</bcf:entrytype> + <bcf:entrytype>inreference</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>booksubtitle</bcf:field> + <bcf:field>booktitle</bcf:field> + <bcf:field>booktitleaddon</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>dataset</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>manual</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>edition</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>misc</bcf:entrytype> + <bcf:entrytype>software</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>howpublished</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>online</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>patent</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>holder</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>periodical</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>editoratype</bcf:field> + <bcf:field>editorbtype</bcf:field> + <bcf:field>editorctype</bcf:field> + <bcf:field>issn</bcf:field> + <bcf:field>issue</bcf:field> + <bcf:field>issuesubtitle</bcf:field> + <bcf:field>issuetitle</bcf:field> + <bcf:field>issuetitleaddon</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>yeardivision</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>mvproceedings</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>eventday</bcf:field> + <bcf:field>eventendday</bcf:field> + <bcf:field>eventendhour</bcf:field> + <bcf:field>eventendminute</bcf:field> + <bcf:field>eventendmonth</bcf:field> + <bcf:field>eventendsecond</bcf:field> + <bcf:field>eventendtimezone</bcf:field> + <bcf:field>eventendyear</bcf:field> + <bcf:field>eventendyeardivision</bcf:field> + <bcf:field>eventhour</bcf:field> + <bcf:field>eventminute</bcf:field> + <bcf:field>eventmonth</bcf:field> + <bcf:field>eventsecond</bcf:field> + <bcf:field>eventtimezone</bcf:field> + <bcf:field>eventyear</bcf:field> + <bcf:field>eventyeardivision</bcf:field> + <bcf:field>eventtitle</bcf:field> + <bcf:field>eventtitleaddon</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>venue</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>proceedings</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>eventday</bcf:field> + <bcf:field>eventendday</bcf:field> + <bcf:field>eventendhour</bcf:field> + <bcf:field>eventendminute</bcf:field> + <bcf:field>eventendmonth</bcf:field> + <bcf:field>eventendsecond</bcf:field> + <bcf:field>eventendtimezone</bcf:field> + <bcf:field>eventendyear</bcf:field> + <bcf:field>eventendyeardivision</bcf:field> + <bcf:field>eventhour</bcf:field> + <bcf:field>eventminute</bcf:field> + <bcf:field>eventmonth</bcf:field> + <bcf:field>eventsecond</bcf:field> + <bcf:field>eventtimezone</bcf:field> + <bcf:field>eventyear</bcf:field> + <bcf:field>eventyeardivision</bcf:field> + <bcf:field>eventtitle</bcf:field> + <bcf:field>eventtitleaddon</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>venue</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>inproceedings</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>booksubtitle</bcf:field> + <bcf:field>booktitle</bcf:field> + <bcf:field>booktitleaddon</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editortype</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>eventday</bcf:field> + <bcf:field>eventendday</bcf:field> + <bcf:field>eventendhour</bcf:field> + <bcf:field>eventendminute</bcf:field> + <bcf:field>eventendmonth</bcf:field> + <bcf:field>eventendsecond</bcf:field> + <bcf:field>eventendtimezone</bcf:field> + <bcf:field>eventendyear</bcf:field> + <bcf:field>eventendyeardivision</bcf:field> + <bcf:field>eventhour</bcf:field> + <bcf:field>eventminute</bcf:field> + <bcf:field>eventmonth</bcf:field> + <bcf:field>eventsecond</bcf:field> + <bcf:field>eventtimezone</bcf:field> + <bcf:field>eventyear</bcf:field> + <bcf:field>eventyeardivision</bcf:field> + <bcf:field>eventtitle</bcf:field> + <bcf:field>eventtitleaddon</bcf:field> + <bcf:field>isbn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>venue</bcf:field> + <bcf:field>volume</bcf:field> + <bcf:field>volumes</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>report</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>institution</bcf:field> + <bcf:field>isrn</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>number</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>version</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>thesis</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>eid</bcf:field> + <bcf:field>institution</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>pages</bcf:field> + <bcf:field>pagetotal</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + </bcf:entryfields> + <bcf:entryfields> + <bcf:entrytype>unpublished</bcf:entrytype> + <bcf:field>addendum</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>eventday</bcf:field> + <bcf:field>eventendday</bcf:field> + <bcf:field>eventendhour</bcf:field> + <bcf:field>eventendminute</bcf:field> + <bcf:field>eventendmonth</bcf:field> + <bcf:field>eventendsecond</bcf:field> + <bcf:field>eventendtimezone</bcf:field> + <bcf:field>eventendyear</bcf:field> + <bcf:field>eventendyeardivision</bcf:field> + <bcf:field>eventhour</bcf:field> + <bcf:field>eventminute</bcf:field> + <bcf:field>eventmonth</bcf:field> + <bcf:field>eventsecond</bcf:field> + <bcf:field>eventtimezone</bcf:field> + <bcf:field>eventyear</bcf:field> + <bcf:field>eventyeardivision</bcf:field> + <bcf:field>eventtitle</bcf:field> + <bcf:field>eventtitleaddon</bcf:field> + <bcf:field>howpublished</bcf:field> + <bcf:field>language</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>pubstate</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>venue</bcf:field> + </bcf:entryfields> + <bcf:multiscriptfields> + <bcf:field>abstract</bcf:field> + <bcf:field>addendum</bcf:field> + <bcf:field>afterword</bcf:field> + <bcf:field>annotator</bcf:field> + <bcf:field>author</bcf:field> + <bcf:field>bookauthor</bcf:field> + <bcf:field>booksubtitle</bcf:field> + <bcf:field>booktitle</bcf:field> + <bcf:field>booktitleaddon</bcf:field> + <bcf:field>chapter</bcf:field> + <bcf:field>commentator</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>editora</bcf:field> + <bcf:field>editorb</bcf:field> + <bcf:field>editorc</bcf:field> + <bcf:field>foreword</bcf:field> + <bcf:field>holder</bcf:field> + <bcf:field>institution</bcf:field> + <bcf:field>introduction</bcf:field> + <bcf:field>issuesubtitle</bcf:field> + <bcf:field>issuetitle</bcf:field> + <bcf:field>issuetitleaddon</bcf:field> + <bcf:field>journalsubtitle</bcf:field> + <bcf:field>journaltitle</bcf:field> + <bcf:field>journaltitleaddon</bcf:field> + <bcf:field>location</bcf:field> + <bcf:field>mainsubtitle</bcf:field> + <bcf:field>maintitle</bcf:field> + <bcf:field>maintitleaddon</bcf:field> + <bcf:field>nameaddon</bcf:field> + <bcf:field>note</bcf:field> + <bcf:field>organization</bcf:field> + <bcf:field>origlanguage</bcf:field> + <bcf:field>origlocation</bcf:field> + <bcf:field>origpublisher</bcf:field> + <bcf:field>origtitle</bcf:field> + <bcf:field>part</bcf:field> + <bcf:field>publisher</bcf:field> + <bcf:field>relatedstring</bcf:field> + <bcf:field>series</bcf:field> + <bcf:field>shortauthor</bcf:field> + <bcf:field>shorteditor</bcf:field> + <bcf:field>shorthand</bcf:field> + <bcf:field>shortjournal</bcf:field> + <bcf:field>shortseries</bcf:field> + <bcf:field>shorttitle</bcf:field> + <bcf:field>sortname</bcf:field> + <bcf:field>sortshorthand</bcf:field> + <bcf:field>sorttitle</bcf:field> + <bcf:field>subtitle</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>titleaddon</bcf:field> + <bcf:field>translator</bcf:field> + <bcf:field>venue</bcf:field> + </bcf:multiscriptfields> + <bcf:constraints> + <bcf:entrytype>article</bcf:entrytype> + <bcf:entrytype>book</bcf:entrytype> + <bcf:entrytype>inbook</bcf:entrytype> + <bcf:entrytype>bookinbook</bcf:entrytype> + <bcf:entrytype>suppbook</bcf:entrytype> + <bcf:entrytype>booklet</bcf:entrytype> + <bcf:entrytype>collection</bcf:entrytype> + <bcf:entrytype>incollection</bcf:entrytype> + <bcf:entrytype>suppcollection</bcf:entrytype> + <bcf:entrytype>manual</bcf:entrytype> + <bcf:entrytype>misc</bcf:entrytype> + <bcf:entrytype>mvbook</bcf:entrytype> + <bcf:entrytype>mvcollection</bcf:entrytype> + <bcf:entrytype>online</bcf:entrytype> + <bcf:entrytype>patent</bcf:entrytype> + <bcf:entrytype>periodical</bcf:entrytype> + <bcf:entrytype>suppperiodical</bcf:entrytype> + <bcf:entrytype>proceedings</bcf:entrytype> + <bcf:entrytype>inproceedings</bcf:entrytype> + <bcf:entrytype>reference</bcf:entrytype> + <bcf:entrytype>inreference</bcf:entrytype> + <bcf:entrytype>report</bcf:entrytype> + <bcf:entrytype>set</bcf:entrytype> + <bcf:entrytype>thesis</bcf:entrytype> + <bcf:entrytype>unpublished</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:fieldxor> + <bcf:field>date</bcf:field> + <bcf:field>year</bcf:field> + </bcf:fieldxor> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>set</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>entryset</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>article</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>journaltitle</bcf:field> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>book</bcf:entrytype> + <bcf:entrytype>mvbook</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>inbook</bcf:entrytype> + <bcf:entrytype>bookinbook</bcf:entrytype> + <bcf:entrytype>suppbook</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>booktitle</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>booklet</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:fieldor> + <bcf:field>author</bcf:field> + <bcf:field>editor</bcf:field> + </bcf:fieldor> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>collection</bcf:entrytype> + <bcf:entrytype>reference</bcf:entrytype> + <bcf:entrytype>mvcollection</bcf:entrytype> + <bcf:entrytype>mvreference</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>editor</bcf:field> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>incollection</bcf:entrytype> + <bcf:entrytype>suppcollection</bcf:entrytype> + <bcf:entrytype>inreference</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>editor</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>booktitle</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>dataset</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>manual</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>misc</bcf:entrytype> + <bcf:entrytype>software</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>online</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>title</bcf:field> + <bcf:fieldor> + <bcf:field>url</bcf:field> + <bcf:field>doi</bcf:field> + <bcf:field>eprint</bcf:field> + </bcf:fieldor> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>patent</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>number</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>periodical</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>editor</bcf:field> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>proceedings</bcf:entrytype> + <bcf:entrytype>mvproceedings</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>inproceedings</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>booktitle</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>report</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>institution</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>thesis</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + <bcf:field>type</bcf:field> + <bcf:field>institution</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:entrytype>unpublished</bcf:entrytype> + <bcf:constraint type="mandatory"> + <bcf:field>author</bcf:field> + <bcf:field>title</bcf:field> + </bcf:constraint> + </bcf:constraints> + <bcf:constraints> + <bcf:constraint type="data" datatype="isbn"> + <bcf:field>isbn</bcf:field> + </bcf:constraint> + <bcf:constraint type="data" datatype="issn"> + <bcf:field>issn</bcf:field> + </bcf:constraint> + <bcf:constraint type="data" datatype="ismn"> + <bcf:field>ismn</bcf:field> + </bcf:constraint> + <bcf:constraint type="data" datatype="pattern" pattern="(?:sf|sm|sn|pf|pm|pn|pp)"> + <bcf:field>gender</bcf:field> + </bcf:constraint> + </bcf:constraints> + </bcf:datamodel> + <!-- CITATION DATA --> + <!-- SECTION 0 --> + <bcf:bibdata section="0"> + <bcf:datasource type="file" datatype="bibtex" glob="false">uni.bib</bcf:datasource> + </bcf:bibdata> + <bcf:section number="0"> + <bcf:citekey order="1" intorder="1">andriushchenko2023sgd</bcf:citekey> + <bcf:citekey order="2" intorder="1">andriushchenko2023sgd</bcf:citekey> + <bcf:citekey order="3" intorder="1">andriushchenko2023sgd</bcf:citekey> + </bcf:section> + <!-- SORTING TEMPLATES --> + <bcf:sortingtemplate name="none"> + <bcf:sort order="1"> + <bcf:sortitem order="1">citeorder</bcf:sortitem> + </bcf:sort> + <bcf:sort order="2"> + <bcf:sortitem order="1">intciteorder</bcf:sortitem> + </bcf:sort> + </bcf:sortingtemplate> + <!-- DATALISTS --> + <bcf:datalist section="0" + name="none/global//global/global" + type="entry" + sortingtemplatename="none" + sortingnamekeytemplatename="global" + labelprefix="" + uniquenametemplatename="global" + labelalphanametemplatename="global"> + </bcf:datalist> +</bcf:controlfile> diff --git a/opt_sem/pres/build/pres1.blg b/opt_sem/pres/build/pres1.blg @@ -0,0 +1,15 @@ +[0] Config.pm:307> INFO - This is Biber 2.19 +[0] Config.pm:310> INFO - Logfile is 'build/pres1.blg' +[86] biber:340> INFO - === Mon Oct 30, 2023, 09:21:06 +[101] Biber.pm:419> INFO - Reading 'build/pres1.bcf' +[170] Biber.pm:979> INFO - Found 1 citekeys in bib section 0 +[188] Biber.pm:4419> INFO - Processing section 0 +[198] Biber.pm:4610> INFO - Looking for bibtex file 'uni.bib' for section 0 +[198] bibtex.pm:1713> INFO - LaTeX decoding ... +[200] bibtex.pm:1519> INFO - Found BibTeX data source 'uni.bib' +[240] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'normalization = NFD' with 'normalization = prenormalized' +[240] UCollate.pm:68> INFO - Overriding locale 'en-US' defaults 'variable = shifted' with 'variable = non-ignorable' +[240] Biber.pm:4239> INFO - Sorting list 'none/global//global/global' of type 'entry' with template 'none' and locale 'en-US' +[240] Biber.pm:4245> INFO - No sort tailoring available for locale 'en-US' +[241] bbl.pm:660> INFO - Writing 'build/pres1.bbl' with encoding 'UTF-8' +[242] bbl.pm:763> INFO - Output to build/pres1.bbl diff --git a/opt_sem/pres/build/pres1.fdb_latexmk b/opt_sem/pres/build/pres1.fdb_latexmk @@ -0,0 +1,305 @@ +# Fdb version 4 +["biber build/pres1"] 1698657665 "build/pres1.bcf" "build/pres1.bbl" "build/pres1" 1698657668 0 + "./uni.bib" 1698653418 301 a730727ca96596cb9bb95b781593e028 "" + "build/pres1.bcf" 1698657668 107118 226ad67bdc77ee07a51f221f54186930 "pdflatex" + (generated) + "build/pres1.bbl" + "build/pres1.blg" + (rewritten before read) +["pdflatex"] 1698657666 "pres1.tex" "build/pres1.pdf" "pres1" 1698657668 0 + 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+\addbibresource{uni.bib} + +\setbeamertemplate{endpage}{% + \begin{frame} + \centering + \Large \emph{To be continued\ldots} + + \vspace{1cm} + + \centering + \Large \emph{Thank You!} + \end{frame} +} + +\AtEndDocument{\usebeamertemplate{endpage}} + +% vertical separator macro +\newcommand{\vsep}{ + \column{0.0\textwidth} + \begin{tikzpicture} + \draw[very thick,black!10] (0,0) -- (0,7.3); + \end{tikzpicture} +} +\setlength{\mathindent}{0pt} + +% Beamer theme +\usetheme{UniVienna} +\usefonttheme[onlysmall]{structurebold} +\mode<presentation> +\setbeamercovered{transparent=10} + +\title +{SGD with Large Step Sizes Lears Sparse Features} +\subtitle{Seminar Optimization} +\author[Popović Milutin] +{Popović Milutin\newline\newline Supervisor: Radu Ioan Bot} +\date{31. October 2023} + +\begin{document} + \begin{frame} + \titlepage + \end{frame} + + \begin{frame}{SGD (Stochastic Gradient Descent} + \begin{itemize} + \item Objective is to minimize functions of the + form + \begin{align*} + \hspace{0.3\linewidth} + f(x) = \frac{1}{n} \sum_{i=1}^{n} f_i(x) + \end{align*} + \end{itemize} + \end{frame} + + \begin{frame}{SGD (Stochastic gradient descent)} + \begin{itemize} + \item Training Data: + \begin{align*} + \hspace{0.3\linewidth} + \{(x_1, y_1),\ldots,(x_n,y_n)\} \in \mathbb{R}^{d} \times + \mathcal{Y} + \end{align*} + \item \mbox{}\onslide<2->{In large-scale ML: large dimension $d$\newline + and large number of traning data $n$.} + \end{itemize} + \end{frame} + + \begin{frame}{SGD (Stochastic gradient descent)} + Classical examples of fitting the data via minimizing: + \begin{itemize} + \item \mbox{}\onslide<2->{Least Squares + \begin{align*} + \hspace{0.3\linewidth} + \frac{1}{n} \| Ax - b \|_2^2 =\frac{1}{n}\sum_{i=1}^n(a_i^T x - b_i)^2 + \end{align*}} + \item \mbox{}\onslide<3->{Support Vector Machine (SVM): + \begin{align*} + \hspace{0.3\linewidth} + \frac{1}{2}||x||_2^2 + \frac{C}{n} \sum_i^n max(0, 1 - y_i(x^T a_i + b)) + \end{align*}} + \item \mbox{}\onslide<4->{Deep Neural Nets + \begin{align*} + \hspace{0.3\linewidth} + \frac{1}{n} \sum_i^n \text{loss}(y_i, DNN(x; a_i)) + \end{align*}} + + \end{itemize} + \end{frame} + + \begin{frame}{SGD (Stochastic gradient descent)} + \begin{itemize} + \item Common pattern: + \begin{align*} + \hspace{0.3\linewidth} + f(x) = \frac{1}{n} \sum_{i=1}^{n} f_i(x) + \end{align*} + \end{itemize} + \end{frame} + + \begin{frame}{GD vs SGD} + \begin{itemize} + \item \mbox{}\onslide<2->{GD would compute the gradient of every $f_i(x)$ to update the + next iterate} + \item \mbox{}\onslide<3->{SGD picks a pseudorandom $i(r) \in \{1, + 2, \ldots, n\}$} + \item \mbox{}\onslide<4->{then uses only $\nabla f_{i(r)}(x_k)$ as its descent + direction + \begin{align*} + \hspace{0.3\linewidth} + x^{k+1} = x^{k} - t_k \nabla f_{i(r)}(x^{k}) + \end{align*}} + + \item \mbox{}\onslide<5->{ + Key property : $\mathbb{E}[\nabla f_{i(r)}(x)] = \nabla f(x)$} + \item \mbox{}\onslide<5->{ + $\nabla f_{i(r)}(x)$ is an unbiased estimator ! + } + \end{itemize} + \end{frame} + + \begin{frame}{Large Stepsizes induce Sparse Features} + \begin{itemize} + \item \mbox{}\onslide<1->{large step sizes -> \textit{loss + stabilization}} + \item \mbox{}\onslide<2->{the longer the larger step size is used + the better the sparse representation} + \end{itemize} + + \begin{figure}[H] + \centering + \includegraphics[width=0.9\textwidth]{./pics/resnet18.png} + \caption{ResNet-18 (Residual Network with 18 layers) trained on + CIFAR-10 (60k 32x32 images)} \cite{andriushchenko2023sgd} + \end{figure} + \end{frame} + + \begin{frame}{Bibliography} + \nocite{andriushchenko2023sgd} + \printbibliography + \end{frame} +\end{document} diff --git a/opt_sem/pres/pres_intro.md b/opt_sem/pres/pres_intro.md @@ -0,0 +1,86 @@ +# SGD with Large Step Sizes Learns Sparse Features + +## WHY? + +Setup: + +Training data $$ {(x_1, y_1), ..., (x_n, y_n)} \in \R^{d} x Y$$ +large-scale ML: large dimension $$d$$, large number of training data $$n$$ + +Classic examples for fitting the data: + +Least squares: $$1/n || Ax - b ||_2^2 =1/n \sum_i^n(a_i^T x - b_i)^2 = 1/n\sum_i^n f_i(x)$$ + +Support Vector Machine (SVM): $$1/2||x||_2^2 + C/n \sum_i^n max(0, 1 - y_i(x^T a_i + b))$$ + +Deep Neural Nets $$1/n \sum_i^n loss(y_i, DNN(x; a_i)) = 1/n \sum_i^n f_(x)$$ + + +All of these optimization problems have the common feature $$1/n \sum_i^n f_i(x)$$ + +So instead of computing at each step the gradient of all the f_i functions we +pick only one (unifrom distribution). + +## SGD vs GD + +We want to minimize functions of the form $$n \sum_{i}^{n} f_i(x)$$ + +GD would compute the gradient of every term, updates the next iterate + +SGD pics a uniformly random $$ i(r) \in \{1, 2, ..., n\} $$ -> +f_{i(k)} and computes its gradient then updates the next iterate + + x^{k+1} = x^{k} - t_k * \nabla f_{i(r)}(x^k) + +Key property : Expectation $$ E[\nabla f_{i(r)}(x)] = \nabla f(x) $$ + is an unbiased estimator !!! + +There are two options in choosing: +Randomly pick an index i + 1. with replacement until the epoch is filled each time + 2. without replacement + +All toolkits use Option 2.! +All papers use Option 1., because its better for analyzing! + +## Large Stepsizes induce Sparse Features? + +"sparse" in NN-terminolog meaining that for a feature vector \psi(x) +only a few features are active and others are 0. + +Using large step sizes often leads iterates to jump = `loss stabilization` +this is the phase of large step sizes where the loss seams to be on average +constant this induces a hidden dynamics to ward simple predictors + +The longer a larger steps size is used the better the implicit regularization +can operate and find sparse representations. + +Justification: Theoretically on simple NN models (Diagonal linear networks, +ReLU networks) and qualitatively with +stochastic processes + + Picture! + +Residual Network 18 Layers trained on CIFAR-10 (60k 32x32 images) for 100 +epochs left training loss, right test error + +Two key phases regarding the large step size: + 1. after the start of training loss remains constant (loss stabilization) + 2. despite no progress, running this phase for longer leads to better + generalization (hidden dynamics) + + +## To be continued... + + + + + + + + + + +#REFS +https://fa.bianp.net/teaching/2018/eecs227at/stochastic_gradient.html +https://www.youtube.com/watch?v=k3AiUhwHQ28 diff --git a/opt_sem/pres/uni.bib b/opt_sem/pres/uni.bib @@ -0,0 +1,8 @@ +@misc{andriushchenko2023sgd, + title={SGD with Large Step Sizes Learns Sparse Features}, + author={Maksym Andriushchenko and Aditya Varre and Loucas Pillaud-Vivien and Nicolas Flammarion}, + year={2023}, + eprint={2210.05337}, + archivePrefix={arXiv}, + primaryClass={cs.LG} +} diff --git a/opt_sem/understanding_machine_learning.pdf b/opt_sem/understanding_machine_learning.pdf Binary files differ.
