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Combinatorial Optimization (CO) problems over graphs appear routinely in many applications such as in optimizing traffic, viral marketing in social networks, and matching for job allocation.
Adagcn: Adaboosting graph convolutional networks into deep models
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Learning multi-stage sparsification for maximum clique enumeration
Grassia, M.; Lauri, J.; Dutta, S.; and Ajwani, D. 2019 · 1910
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The regression analysis of binary sequences
Cox, D. R. 1958 · 1958
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Approximation algorithms for NP-hard problems
Hochba, D. S. 1997 · 1997
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Combinatorial optimization: algorithms and complexity
Papadimitriou, C. H.; and Steiglitz, K. 1998 · 1998
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A short introduction to boosting
Freund, Y.; Schapire, R.; and Abe, N. 1999 · 1999
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Learning fine-grained search space pruning and heuristics for combinatorial optimization
Lauri, J.; Dutta, S.; Grassia, M.; and Ajwani, D. 2020 · 2001
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Approximation algorithms
Vazirani, V. V. 2001 · 2001
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Statistical mechanics of complex networks
Albert, R.; and Barabási, A.-L. 2002 · 2002
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Stochastic local search: Foundations and applications
Hoos, H. H.; and Stützle, T. 2004 · 2004
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Collective classification in network data
Sen, P.; Namata, G.; Bilgic, M.; Getoor, L.; Galligher, B.; and Eliassi-Rad, T. 2008 · 2008
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Inapproximability of hypergraph vertex cover and applications to scheduling problems
Bansal, N.; and Khot, S. 2010 · 2010
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An automatic method for solving discrete programming problems
Land, A. H.; and Doig, A. G. 2010 · 2010
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Rectified linear units improve restricted boltzmann machines
Nair, V.; and Hinton, G. E. 2010 · 2010
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The design of approximation algorithms
Williamson, D. P.; and Shmoys, D. B. 2011 · 2011
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Fast local search for the maximum independent set problem
Andrade, D. V.; Resende, M. G.; and Werneck, R. F. 2012 · 2012
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Recommendations to boost content spread in social networks
Chaoji, V.; Ranu, S.; Rastogi, R.; and Bhatt, R. 2012 · 2012
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Neural machine translation by jointly learning to align and translate
Bahdanau, D.; Cho, K.; and Bengio, Y. 2014 · 2014
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SNAP Datasets: Stanford Large Network Dataset Collection
Leskovec, J.; and Krevl, A. 2014 · 2014
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Distilling the knowledge in a neural network
Hinton, G.; Vinyals, O.; and Dean, J. 2015 · 2015
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Pointer networks
Optimizing Network Structure for Preventative Health
Wilder, B.; Ou, H.-C.; de la Haye, K.; and Tambe, M. 2018 · 2018
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Online vehicle routing with neural combinatorial optimization and deep reinforcement learning
James, J.; Yu, W.; and Gu, J. 2019 · 2019
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Learning what to defer for maximum independent sets
Ahn, S.; Seo, Y.; and Shin, J. 2020 · 2020
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Exploratory combinatorial optimization with reinforcement learning
Barrett, T.; Clements, W.; Foerster, J.; and Lvovsky, A. 2020 · 2020
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Message passing neural networks
Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; and Dahl, G. E. 2020 · 2020
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Automated design of thousands of nonrepetitive parts for engineering stable genetic systems
Hossain, A.; Lopez, E.; Halper, S. M.; Cetnar, D. P.; Reis, A. C.; Strickland, D.; Klavins, E.; and Salis, H. M. 2020 · 2020
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Vinyals, O.; Fortunato, M.; and Jaitly, N. 2015 · 2015
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Neural combinatorial optimization with reinforcement learning
Bello, I.; Pham, H.; Le, Q. V.; Norouzi, M.; and Bengio, S. 2016 · 2016
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Discriminative embeddings of latent variable models for structured data
Dai, H.; Dai, B.; and Song, L. 2016 · 2016
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Semi-supervised classification with graph convolutional networks
Kipf, T. N.; and Welling, M. 2016 · 2016
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Tri-party deep network representation
Pan, S.; Wu, J.; Zhu, X.; Zhang, C.; and Wang, Y. 2016 · 2016
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Inductive representation learning on large graphs
Hamilton, W.; Ying, Z.; and Leskovec, J. 2017 · 2017
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Learning combinatorial optimization algorithms over graphs
Khalil, E.; Dai, H.; Zhang, Y.; Dilkina, B.; and Song, L. 2017 · 2017
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Gcomb: Learning budget-constrained combinatorial algorithms over billion-sized graphs
Manchanda, S.; Mittal, A.; Dhawan, A.; Medya, S.; Ranu, S.; and Singh, A. 2020 · 2020
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Tinygnn: Learning efficient graph neural networks
Yan, B.; Wang, C.; Guo, G.; and Lou, Y. 2020 · 2020
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Distilling Knowledge From Graph Convolutional Networks
Yang, Y.; Qiu, J.; Song, M.; Tao, D.; and Wang, X. 2020 · 2020
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Graph-Free Knowledge Distillation for Graph Neural Networks
Deng, X.; and Zhang, Z. 2021 · 2021
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Learning to sparsify travelling salesman problem instances
Fitzpatrick, J.; Ajwani, D.; and Carroll, P. 2021 · 2021
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Ibm ilog cplex optimization studio
Nickel, S.; Steinhardt, C.; Schlenker, H.; Burkart, W.; Reuter-Oppermann, M.; Nickel, S.; Steinhardt, C.; Schlenker, H.; Burkart, W.; and Reuter-Oppermann, M. 2021 · 2021
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Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation
Zhang, S.; Liu, Y.; Sun, Y.; and Shah, N. 2021 · 2021
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Boosting graph neural networks via adaptive knowledge distillation
Guo, Z.; Zhang, C.; Fan, Y.; Tian, Y.; Zhang, C.; and Chawla, N. V. 2023 · 2023
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