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The Machine Learning for Combinatorial Optimization (ML4CO) NeurIPS 2021 competition aims to improve state-of-the-art combinatorial optimization solvers by replacing key heuristic components with machine learning models.
Experiments in mixed-integer linear programming
Michel Bénichou, Jean-Michel Gauthier, Paul Girodet, Gerard Hentges, Gerard Ribière, and O Vincent · 1971
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An analysis of degeneracy
Harvey J Greenberg · 1986
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A framework for behavioural cloning
Michael Bain and Claude Sammut · 1995
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A computational study of search strategies for mixed integer programming
Jeff T Linderoth and Martin WP Savelsbergh · 1999
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Ensemble methods in machine learning
Thomas G Dietterich · 2000
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Branching rules revisited
Tobias Achterberg, Thorsten Koch, and Alexander Martin · 2005
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2008
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Search-based structured prediction
Hal Daumé, John Langford, and Daniel Marcu · 2009
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An automatic method for solving discrete programming problems
Ailsa H Land and Alison G Doig · 2010
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Efficient reductions for imitation learning
Stéphane Ross and Drew Bagnell · 2010
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A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Semi-supervised classification with graph convolutional networks
On learning and branching: a survey
Andrea Lodi and Giulia Zarpellon · 2017
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Antti Tarvainen and Harri Valpola · 2017
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Born again neural networks
Tommaso Furlanello, Zachary Lipton, Michael Tschannen, Laurent Itti, and Anima Anandkumar · 2018
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Averaging weights leads to wider optima and better generalization
Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry Vetrov, and Andrew Gordon Wilson · 2018
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Learning to run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael F Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, et al · 2018
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Thomas N Kipf and Max Welling · 2016
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Snapshot ensembles: Train 1, get m for free
Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E Hopcroft, and Kilian Q Weinberger · 2017
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Exact combinatorial optimization with graph convolutional neural networks
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, and Andrea Lodi · 2019
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The scip optimization suite 7.0
Gerald Gamrath, Daniel Anderson, Ksenia Bestuzheva, Wei-Kun Chen, Leon Eifler, Maxime Gasse, Patrick Gemander, Ambros Gleixner, Leona Gottwald, Katrin Halbig, et al · 2020
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