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Combinatorial Optimization (CO) has been a long-standing challenging research topic featured by its NP-hard nature.
A relationship between arbitrary positive matrices and doubly stochastic matrices
R. Sinkhorn and A. Rangarajan · 1964
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An analysis of several heuristics for the traveling salesman problem
D. J. Rosenkrantz, R. E. Stearns, and P. M. Lewis, II · 1977
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The polynomial hierarchy and a simple model for competitive analysis
R. G. Jeroslow · 1985
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Computers and Intractability; A Guide to the Theory of NP-Completeness
M. R. Garey and D. S. Johnson · 1990
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Descent approaches for quadratic bilevel programming
L. Vicente, G. Savard, and J. Júdice · 1994
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An effective implementation of the lin–kernighan traveling salesman heuristic
K. Helsgaun · 2000
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The traveling salesman: computational solutions for TSP applications
G. Reinelt · 2003
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DAG Scheduling for Grid Computing Systems
A. Forti · 2006
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Speeding up graph edit distance computation with a bipartite heuristic
K. Riesen, S. Fankhauser, and H. Bunke · 2007
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Iam graph database repository for graph based pattern recognition and machine learning
K. Riesen and H. Bunke · 2008
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Approximate graph edit distance computation by means of bipartite graph matching
K. Riesen and H. Bunke · 2009
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Reweighted random walks for graph matching
M. Cho, J. Lee, and K. M. Lee · 2010
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Outline of an algorithm for integer solutions to linear programs and an algorithm for the mixed integer problem
R. E. Gomory · 2010
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Automated configuration of mixed integer programming solvers
F. Hutter, H. H. Hoos, and K. Leyton-Brown · 2010
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Hydra-mip: Automated algorithm configuration and selection for mixed integer programming
L. Xu, F. Hutter, H. H. Hoos, and K. Leyton-Brown · 2011
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Playing atari with deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller · 2013
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Reasoning with neural tensor networks for knowledge base completion
R. Socher, D. Chen, C. D. Manning, and A. Y. Ng · 2013
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A Taxonomy of Metaheuristics for Bi-level Optimization
E.-G. Talbi · 2013
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Multi-resource packing for cluster schedulers
R. Grandl, G. Ananthanarayanan, S. Kandula, S. Rao, and A. Akella · 2014
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An exact graph edit distance algorithm for solving pattern recognition problems
Z. Abu-Aisheh, R. Raveaux, J.-Y. Ramel, and P. Martineau · 2015
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Trust region policy optimization
J. Schulman, S. Levine, P. Abbeel, M. Jordan, and P. Moritz · 2015
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Pointer networks
O. Vinyals, M. Fortunato, and N. Jaitly · 2015
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Graph edit distance as a quadratic program
S. Bougleux, B. Gaüzere, and L. Brun · 2016
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Discriminative embeddings of latent variable models for structured data
H. Dai, B. Dai, and L. Song · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Learning to branch in mixed integer programming
E. Khalil, P. Le Bodic, L. Song, G. Nemhauser, and B. Dilkina · 2016
Cited alongside, same era.
An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems
K. Helsgaun · 2017
Cited alongside, same era.
Learning combinatorial optimization algorithms over graphs
E. Khalil, H. Dai, Y. Zhang, B. Dilkina, and L. Song · 2017
Cited alongside, same era.
Graph matching networks for learning the similarity of graph structured objects
Y. Li, C. Gu, T. Dullien, O. Vinyals, and P. Kohli · 2019
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A learning-based iterative method for solving vehicle routing problems
H. Lu, X. Zhang, and S. Yang · 2019
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Learning scheduling algorithms for data processing clusters
H. Mao, M. Schwarzkopf, S. B. Venkatakrishnan, Z. Meng, and M. Alizadeh · 2019
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Machine learning for combinatorial optimization: a methodological tour d’horizon
Y. Bengio, A. Lodi, and A. Prouvost · 2020
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Comparing heuristics for graph edit distance computation
D. B. Blumenthal, N. Boria, J. Gamper, S. Bougleux, and L. Brun · 2020
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Graph edit distance reward: Learning to edit scene graph
L. Chen, G. Lin, S. Wang, and Q. Wu · 2020
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Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
Cited alongside, same era.
Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
Cited alongside, same era.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin · 2017
Cited alongside, same era.
A hybrid machine-learning and optimization method to solve bi-level problems
S. A. Bagloee, M. Asadi, M. Sarvi, and M. Patriksson · 2018
Cited alongside, same era.
Combinatorial optimization with graph convolutional networks and guided tree search
Z. Li, Q. Chen, and V. Koltun · 2018
Cited alongside, same era.
Revised note on learning quadratic assignment with graph neural networks
A. Nowak, S. Villar, A. Bandeira, and J. Bruna · 2018
Cited alongside, same era.
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Graph neural architecture search
Y. Gao, H. Yang, P. Zhang, C. Zhou, and Y. Hu · 2020
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Tap-net: transport-and-pack using reinforcement learning
R. Hu, J. Xu, B. Chen, M. Gong, H. Zhang, and H. Huang · 2020
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Erdos goes neural: an unsupervised learning framework for combinatorial optimization on graphs
N. Karalias and A. Loukas · 2020
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Deep reinforcement learning of graph matching
C. Liu, R. Wang, Z. Jiang, and J. Yan · 2020
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Improving learning to branch via reinforcement learning
H. Sun, W. Chen, H. Li, and L. Song · 2020
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Reinforcement learning for integer programming: Learning to cut
Y. Tang, S. Agrawal, and Y. Faenza · 2020
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Combinatorial learning of robust deep graph matching: an embedding based approach
R. Wang, J. Yan, and X. Yang · 2020
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Learning for graph matching and related combinatorial optimization problems
J. Yan, S. Yang, and E. R. Hancock · 2020
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A survey on reinforcement learning for combinatorial optimization
Y. Yang and A. B. Whinston · 2020
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Learning to dispatch for job shop scheduling via deep reinforcement learning
C. Zhang, W. Song, Z. Cao, J. Zhang, P. S. Tan, and X. Chi · 2020
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Generalize a small pre-trained model to arbitrarily large tsp instances
Z.-H. Fu, K.-B. Qiu, and H. Zha · 2021
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R. Liu, J. Gao, J. Zhang, D. Meng, and Z. Lin · 2021
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Neural graph matching network: Learning lawler’s quadratic assignment problem with extension to hypergraph and multiple-graph matching
R. Wang, J. Yan, and X. Yang · 2021
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Combinatorial learning of graph edit distance via dynamic embedding
R. Wang, T. Zhang, T. Yu, J. Yan, and X. Yang · 2021
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Search to aggregate neighborhood for graph neural network
H. Zhao, Q. Yao, and W. Tu · 2021
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