https://m1p.org/index.php?action=history&feed=atom&title=Reasoning_AI_system 2026-04-09T07:25:18Z Revision history for this page on the wiki MediaWiki 1.34.0 https://m1p.org/index.php?title=Reasoning_AI_system&diff=2149&oldid=prev 2025-03-08T15:18:13Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 15:18, 8 March 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l12" >Line 12:</td> <td colspan="2" class="diff-lineno">Line 12:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Сологуб) Algorithms of inductive model generation and transformation 2014 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/PhDThesis/Sologub2013GenerationFinal/diss/PHDpresentation.pdf?format=raw slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Сологуб) Algorithms of inductive model generation and transformation 2014 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/PhDThesis/Sologub2013GenerationFinal/diss/PHDpresentation.pdf?format=raw slides]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Кузнецов) Structure learning drafts [https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/StructureLearning/ link]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Кузнецов) Structure learning drafts [https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/StructureLearning/ link]</div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Requirements for data==</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">1) Collection of unified datasets</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">2) a dataset is a multivariate, or ideally, multidimensional time series;</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">3) are easy to access, update, and augment, without a difficult crawler;</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">4) are fun to visualize;</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">5) are impactful and suggestive to discuss.</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">The candidates are:</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#</ins></div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1991&oldid=prev 2025-02-16T19:27:46Z

<p><span dir="auto"><span class="autocomment">Links to model generation papers</span></span></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 19:27, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l2" >Line 2:</td> <td colspan="2" class="diff-lineno">Line 2:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Disconnected Graph Neural Network 2020 [https://chemrxiv.org/engage/chemrxiv/article-details/60c74e0f9abda2cf1af8d58a paper], [https://github.com/isayevlab/DRACON code]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Nikitin) </ins>Disconnected Graph Neural Network 2020 [https://chemrxiv.org/engage/chemrxiv/article-details/60c74e0f9abda2cf1af8d58a paper], [https://github.com/isayevlab/DRACON code]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Шибаев) Optimal spanning tree reconstruction in symbolic regression 2024 [https://arxiv.org/abs/2406.18612], 2018 [http://www.machinelearning.ru/wiki/images/9/90/Shibaev2018BThesis.pdf thesis][http://www.machinelearning.ru/wiki/images/c/c1/Shibaev2018Presentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Шибаев) Optimal spanning tree reconstruction in symbolic regression 2024 [https://arxiv.org/abs/2406.18612], 2018 [http://www.machinelearning.ru/wiki/images/9/90/Shibaev2018BThesis.pdf thesis][http://www.machinelearning.ru/wiki/images/c/c1/Shibaev2018Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Потанин) Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Потанин) Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1990&oldid=prev 2025-02-16T19:27:22Z

<p><span dir="auto"><span class="autocomment">Links to model generation papers</span></span></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 19:27, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l2" >Line 2:</td> <td colspan="2" class="diff-lineno">Line 2:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Disconnected Graph Neural Network 2020 [https://chemrxiv.org/engage/chemrxiv/article-details/60c74e0f9abda2cf1af8d58a paper], [https://github.com/isayevlab/DRACON code]</ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Шибаев) Optimal spanning tree reconstruction in symbolic regression 2024 [https://arxiv.org/abs/2406.18612], 2018 [http://www.machinelearning.ru/wiki/images/9/90/Shibaev2018BThesis.pdf thesis][http://www.machinelearning.ru/wiki/images/c/c1/Shibaev2018Presentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Шибаев) Optimal spanning tree reconstruction in symbolic regression 2024 [https://arxiv.org/abs/2406.18612], 2018 [http://www.machinelearning.ru/wiki/images/9/90/Shibaev2018BThesis.pdf thesis][http://www.machinelearning.ru/wiki/images/c/c1/Shibaev2018Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Потанин) Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Потанин) Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1989&oldid=prev 2025-02-16T17:52:38Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:52, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l9" >Line 9:</td> <td colspan="2" class="diff-lineno">Line 9:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Кулунчаков) Порождение структурно простых ранжирующих функций для задач информационного поиска 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis], 2015 [http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides], and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Кулунчаков) Порождение структурно простых ранжирующих функций для задач информационного поиска 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis], 2015 [http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides], and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Фадеев) Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># (Фадеев) Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># (Сологуб) Algorithms of inductive model generation and transformation 2014 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># (Сологуб) Algorithms of inductive model generation and transformation 2014 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [<ins class="diffchange diffchange-inline">https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/PhDThesis/Sologub2013GenerationFinal/diss/PHDpresentation.pdf?format=raw </ins>slides<ins class="diffchange diffchange-inline">]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"># (Кузнецов) Structure learning drafts [https://sourceforge.net/p/mlalgorithms/code/HEAD/tree/StructureLearning/ link</ins>]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1988&oldid=prev 2025-02-16T17:41:50Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:41, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l2" >Line 2:</td> <td colspan="2" class="diff-lineno">Line 2:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==Links to model generation papers==</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Шибаев) </ins>Optimal spanning tree reconstruction in symbolic regression <ins class="diffchange diffchange-inline">2024 </ins>[https://arxiv.org/abs/2406.18612<ins class="diffchange diffchange-inline">], 2018 [http://www.machinelearning.ru/wiki/images/9/90/Shibaev2018BThesis.pdf thesis][http://www.machinelearning.ru/wiki/images/c/c1/Shibaev2018Presentation.pdf slides</ins>]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Потанин) </ins>Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Варфоломеева) </ins>Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Рудой) </ins>Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Структурное обучение для генерации моделей 2015 [http://www.machinelearning.ru/wiki/images/6/69/BochkarevArtemMasterThesisText_v3.pdf thesis],  Порождение экспертно-интерпретируемых моделей петрофизических измерений 2018 [http://www.machinelearning.ru/wiki/images/3/3e/BochkarevPresentation.pdf slides], [http://www.machinelearning.ru/wiki/images/b/bb/BochkarevArtemMasterThesis_v3.pdf slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Бочкарев) </ins>Структурное обучение для генерации моделей 2015 [http://www.machinelearning.ru/wiki/images/6/69/BochkarevArtemMasterThesisText_v3.pdf thesis],  Порождение экспертно-интерпретируемых моделей петрофизических измерений 2018 [http://www.machinelearning.ru/wiki/images/3/3e/BochkarevPresentation.pdf slides], [http://www.machinelearning.ru/wiki/images/b/bb/BochkarevArtemMasterThesis_v3.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Порождение структурно простых ранжирующих функций для задач информационного поиска <del class="diffchange diffchange-inline">2015, </del>2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] <del class="diffchange diffchange-inline">2017</del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Кулунчаков) </ins>Порождение структурно простых ранжирующих функций для задач информационного поиска 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis]<ins class="diffchange diffchange-inline">, 2015 </ins>[http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides]<ins class="diffchange diffchange-inline">, </ins>and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Фадеев) </ins>Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># <del class="diffchange diffchange-inline"> </del>Algorithms of inductive model generation and transformation <del class="diffchange diffchange-inline">2018 </del>[https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">(Сологуб) </ins>Algorithms of inductive model generation and transformation <ins class="diffchange diffchange-inline">2014 </ins>[https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1987&oldid=prev 2025-02-16T17:32:36Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:32, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l6" >Line 6:</td> <td colspan="2" class="diff-lineno">Line 6:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># <del class="diffchange diffchange-inline"> Порождение экспертно-интерпретируемых </del>моделей <del class="diffchange diffchange-inline">петрофизических измерений 2018  </del>[http://www.machinelearning.ru/wiki/images/<del class="diffchange diffchange-inline">3</del>/<del class="diffchange diffchange-inline">3e</del>/<del class="diffchange diffchange-inline">BochkarevPresentation</del>.pdf <del class="diffchange diffchange-inline">slides</del>]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline">Структурное обучение для генерации </ins>моделей <ins class="diffchange diffchange-inline">2015 </ins>[http://www.machinelearning.ru/wiki/images/<ins class="diffchange diffchange-inline">6</ins>/<ins class="diffchange diffchange-inline">69</ins>/<ins class="diffchange diffchange-inline">BochkarevArtemMasterThesisText_v3</ins>.pdf <ins class="diffchange diffchange-inline">thesis</ins>]<ins class="diffchange diffchange-inline">,  Порождение экспертно-интерпретируемых </ins>моделей <ins class="diffchange diffchange-inline">петрофизических измерений 2018 </ins>[http://www.machinelearning.ru/wiki/images/<ins class="diffchange diffchange-inline">3</ins>/<ins class="diffchange diffchange-inline">3e</ins>/<ins class="diffchange diffchange-inline">BochkarevPresentation</ins>.pdf <ins class="diffchange diffchange-inline">slides</ins>]<ins class="diffchange diffchange-inline">, </ins>[http://www.machinelearning.ru/wiki/images/b/bb/BochkarevArtemMasterThesis_v3.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># Структурное обучение для генерации </del>моделей <del class="diffchange diffchange-inline">2015 </del>[http://www.machinelearning.ru/wiki/images/<del class="diffchange diffchange-inline">6</del>/<del class="diffchange diffchange-inline">69</del>/<del class="diffchange diffchange-inline">BochkarevArtemMasterThesisText_v3</del>.pdf <del class="diffchange diffchange-inline">thesis</del>] [http://www.machinelearning.ru/wiki/images/b/bb/BochkarevArtemMasterThesis_v3.pdf slides]</div></td><td colspan="2"> </td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Порождение структурно простых ранжирующих функций для задач информационного поиска 2015, 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] 2017</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Порождение структурно простых ранжирующих функций для задач информационного поиска 2015, 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] 2017</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#  Algorithms of inductive model generation and transformation 2018 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#  Algorithms of inductive model generation and transformation 2018 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1986&oldid=prev 2025-02-16T17:31:00Z

<p><span dir="auto"><span class="autocomment">Links to model generation papers</span></span></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:31, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l4" >Line 4:</td> <td colspan="2" class="diff-lineno">Line 4:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td><td colspan="2"> </td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#  Порождение экспертно-интерпретируемых моделей петрофизических измерений 2018  [http://www.machinelearning.ru/wiki/images/3/3e/BochkarevPresentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>#  Порождение экспертно-интерпретируемых моделей петрофизических измерений 2018  [http://www.machinelearning.ru/wiki/images/3/3e/BochkarevPresentation.pdf slides]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1985&oldid=prev 2025-02-16T17:30:28Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:30, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This page collects links to materials on reasoning AI. The interpretability, or presence of logical deduction here is devoted to Mathematical modeling. The practical goal is to develop an engineering system that delivers simple mathematical models providing datasets with minimum prior knowledge.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This page collects links to materials on reasoning AI. The interpretability, or presence of logical deduction here is devoted to Mathematical modeling. The practical goal is to develop an engineering system that delivers simple mathematical models providing datasets with minimum prior knowledge.</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">*  Def. interpretability []</del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">==</ins>Links to model generation <ins class="diffchange diffchange-inline">papers==</ins></div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div> </div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"># </ins>Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># </del>Links to model generation <del class="diffchange diffchange-inline">works</del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline"># </ins>Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">* </del>Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td><td colspan="2"> </td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">* </del>Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td colspan="2"> </td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td></tr> <tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l13" >Line 13:</td> <td colspan="2" class="diff-lineno">Line 11:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Порождение структурно простых ранжирующих функций для задач информационного поиска 2015, 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] 2017</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Порождение структурно простых ранжирующих функций для задач информационного поиска 2015, 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] 2017</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div># 2018 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div># <ins class="diffchange diffchange-inline"> Algorithms of inductive model generation and transformation </ins>2018 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1984&oldid=prev 2025-02-16T17:28:56Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:28, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l6" >Line 6:</td> <td colspan="2" class="diff-lineno">Line 6:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2"> </td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</div></td></tr> </table>

Wiki https://m1p.org/index.php?title=Reasoning_AI_system&diff=1983&oldid=prev 2025-02-16T17:28:25Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en-GB"> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">← Older revision</td> <td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 17:28, 16 February 2025</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This page collects links to materials on reasoning AI. The interpretability, or presence of logical deduction here is devoted to Mathematical modeling. The practical goal is to develop an engineering system that delivers simple mathematical models providing datasets with minimum prior knowledge.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>This page collects links to materials on reasoning AI. The interpretability, or presence of logical deduction here is devoted to Mathematical modeling. The practical goal is to develop an engineering system that delivers simple mathematical models providing datasets with minimum prior knowledge.</div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">*  Def. interpretability []</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Links to model generation works</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Optimal spanning tree reconstruction in symbolic regression [https://arxiv.org/abs/2406.18612]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">* Additive regularization schedule for neural architecture search [https://arxiv.org/abs/2406.12992]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Методы структурного обучения для построения прогностических моделей 2012 [http://www.machinelearning.ru/wiki/images/f/f2/Varfolomeeva2013Diploma.pdf thesis],  [http://www.machinelearning.ru/wiki/images/a/a3/Varfolomeeva2013Presentation.pdf slides], 2015 [http://www.machinelearning.ru/wiki/images/2/27/Varfolomeeva2015MsThesis.pdf thesis],</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">[http://www.machinelearning.ru/wiki/images/5/53/Varfolomeeva2015MsPresentation.pdf slides]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Алгоритмы индуктивного порождения и упрощения 2014 [http://www.machinelearning.ru/wiki/images/0/02/Rudoy2014ModelsSelection.pdf thesis], [http://www.machinelearning.ru/wiki/images/0/0e/Rudoy2014ModelsSelectionSlides.pdf slides], 2012 [https://m1p.org/papers/Rudoy2012Generation_Preprint.pdf paper]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">#  Порождение экспертно-интерпретируемых моделей петрофизических измерений 2018  [http://www.machinelearning.ru/wiki/images/3/3e/BochkarevPresentation.pdf slides]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Структурное обучение для генерации моделей 2015 [http://www.machinelearning.ru/wiki/images/6/69/BochkarevArtemMasterThesisText_v3.pdf thesis] [http://www.machinelearning.ru/wiki/images/b/bb/BochkarevArtemMasterThesis_v3.pdf slides]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Порождение структурно простых ранжирующих функций для задач информационного поиска 2015, 2017 [http://www.machinelearning.ru/wiki/images/9/9e/Kulunchakov2017RankingBySimpleFun.pdf thesis][http://www.machinelearning.ru/wiki/images/f/f4/PresentationKulunchakov2015Ranking.pdf slides] and [https://www.researchgate.net/publication/316806366_Generation_of_simple_structured_Information_Retrieval_functions_by_genetic_algorithm_without_stagnation#fullTextFileContent paper] 2017</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># Выбор иерархических моделей  в авторегрессионном прогнозировании, 2013 [http://www.machinelearning.ru/wiki/images/4/40/Fadeev2013MsThesis.pdf thesis], [http://www.machinelearning.ru/wiki/images/4/43/Fadeev2013Presentation.pdf slides]</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"># 2018 [https://m1p.org/papers/Sologub2014Disser-0018d.pdf thesis], [slides]</ins></div></td></tr> </table>

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