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1811.06128
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Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon
15 November 2018
Yoshua Bengio
Andrea Lodi
Antoine Prouvost
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Papers citing
"Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon"
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Title
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Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems
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How Good Is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem
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Yu Zhang
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Deep-Steiner: Learning to Solve the Euclidean Steiner Tree Problem
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Yifan Wang
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Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models
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Luca Franceschi
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Structured Q-learning For Antibody Design
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SyDa
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Learning to Prune Instances of Steiner Tree Problem in Graphs
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Deepak Ajwani
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Self-Supervised Primal-Dual Learning for Constrained Optimization
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Learning with Combinatorial Optimization Layers: a Probabilistic Approach
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19
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Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
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Annealed Training for Combinatorial Optimization on Graphs
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E. Guha
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27
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Adaptive Learning for the Resource-Constrained Classification Problem
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Xiaochen Xian
Kejun Huang
G. Singer
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Supplementing Recurrent Neural Networks with Annealing to Solve Combinatorial Optimization Problems
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Jawaril Munshad Abedin
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18
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0
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Simulation-guided Beam Search for Neural Combinatorial Optimization
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Kevin Tierney
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30
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Neural Topological Ordering for Computation Graphs
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Yang Yang
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Chris Lott
Roberto Bondesan
32
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Learning the Quality of Machine Permutations in Job Shop Scheduling
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Simone Calderara
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16
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Learning to Accelerate Approximate Methods for Solving Integer Programming via Early Fixing
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Baoyuan Wu
21
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Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set
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11
32
0
27 Jun 2022
Learning to Control Local Search for Combinatorial Optimization
Jonas K. Falkner
Daniela Thyssens
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32
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0
27 Jun 2022
NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search
Yi Qin
Ziwei Zhang
Xin Wang
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Temporal Multimodal Multivariate Learning
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Justice Darko
Niharika Deshpande
Venktesh Pandey
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M. Ono
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L. Folsom
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Steve Chien
22
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Machine learning-based patient selection in an emergency department
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M. O'Sullivan
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14
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08 Jun 2022
A Deep Reinforcement Learning Framework For Column Generation
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Zoha Sherkat-Masoumi
26
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On the Generalization of Neural Combinatorial Optimization Heuristics
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Sofia Michel
Darko Drakulic
J. Andreoli
27
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Neural Improvement Heuristics for Graph Combinatorial Optimization Problems
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A. Mendiburu
31
4
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The CLRS Algorithmic Reasoning Benchmark
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Razvan Pascanu
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Charles Blundell
163
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0
31 May 2022
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectories
Christopher W. F. Parsonson
Alexandre Laterre
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19
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MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers
Elias Boutros Khalil
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33
48
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Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration
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Christopher W. F. Parsonson
Alexandre Laterre
29
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27 May 2022
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
Ahmed Abbas
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38
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Learning to branch with Tree MDPs
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Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens
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18
2
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20 May 2022
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
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Equivariant quantum circuits for learning on weighted graphs
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Graph Neural Networks for Propositional Model Counting
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Learning to Solve Vehicle Routing Problems: A Survey
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Neural Combinatorial Optimization: a New Player in the Field
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Fast Continuous and Integer L-shaped Heuristics Through Supervised Learning
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An attention model for the formation of collectives in real-world domains
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Learning for Spatial Branching: An Algorithm Selection Approach
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Expert-Calibrated Learning for Online Optimization with Switching Costs
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Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts
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Pareto Set Learning for Neural Multi-objective Combinatorial Optimization
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A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks
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