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Machine Learning for Combinatorial Optimization: a Methodological Tour
  d'Horizon
v1v2 (latest)

Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon

15 November 2018
Yoshua Bengio
Andrea Lodi
Antoine Prouvost
ArXiv (abs)PDFHTML

Papers citing "Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon"

50 / 567 papers shown
Enhancing Constraint Programming via Supervised Learning for Job Shop
  Scheduling
Enhancing Constraint Programming via Supervised Learning for Job Shop SchedulingKnowledge-Based Systems (KBS), 2022
Yuan Sun
Su Nguyen
D. Thiruvady
Xiaodong Li
Andreas T. Ernst
U. Aickelin
240
6
0
26 Nov 2022
How to predict and optimise with asymmetric error metrics
How to predict and optimise with asymmetric error metrics
M. Abolghasemi
Richard Bean
109
6
0
24 Nov 2022
Actively Learning Costly Reward Functions for Reinforcement Learning
Actively Learning Costly Reward Functions for Reinforcement Learning
André Eberhard
Houssam Metni
G. Fahland
A. Stroh
Pascal Friederich
OffRL
235
1
0
23 Nov 2022
UNSAT Solver Synthesis via Monte Carlo Forest Search
UNSAT Solver Synthesis via Monte Carlo Forest SearchIntegration of AI and OR Techniques in Constraint Programming (CP-AI-OR), 2022
Chris Cameron
Jason S. Hartford
Taylor Lundy
T. Truong
Alan Milligan
Rex Chen
Kevin Leyton-Brown
240
3
0
22 Nov 2022
Arbitrarily Large Labelled Random Satisfiability Formulas for Machine
  Learning Training
Arbitrarily Large Labelled Random Satisfiability Formulas for Machine Learning Training
D. Achlioptas
Amrit Daswaney
Periklis A. Papakonstantinou
NAIBDL
137
0
0
21 Nov 2022
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop
  Scheduling
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop SchedulingInternational Conference on Learning Representations (ICLR), 2022
Cong Zhang
Zhiguang Cao
Wen Song
Puay Siew Tan
Jie Zhang
203
23
0
20 Nov 2022
A Survey on Influence Maximization: From an ML-Based Combinatorial
  Optimization
A Survey on Influence Maximization: From an ML-Based Combinatorial OptimizationACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Yandi Li
Haobo Gao
Yunxuan Gao
Jianxiong Guo
Weili Wu
293
65
0
06 Nov 2022
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based
  Imitation Learning
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation LearningAAAI Conference on Artificial Intelligence (AAAI), 2022
Longkang Li
Yaning Tan
Zihao Zhu
Chris H. Q. Ding
Hong Zha
Baoyuan Wu
AI4CE
196
16
0
31 Oct 2022
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks
Learning to Compare Nodes in Branch and Bound with Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Abdel Ghani Labassi
Didier Chételat
Andrea Lodi
149
41
0
30 Oct 2022
End-to-End Pareto Set Prediction with Graph Neural Networks for
  Multi-objective Facility Location
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility LocationInternational Conference on Evolutionary Multi-Criterion Optimization (EMO), 2022
Shiqing Liu
Xueming Yan
Yaochu Jin
137
9
0
27 Oct 2022
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear
  Optimization Problems
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization ProblemsInternational Conference on Machine Learning (ICML), 2022
Aaron Ferber
Taoan Huang
Daochen Zha
M. Schubert
Benoit Steiner
B. Dilkina
Yuandong Tian
179
24
0
22 Oct 2022
Machine Learning for K-adaptability in Two-stage Robust Optimization
Machine Learning for K-adaptability in Two-stage Robust OptimizationINFORMS journal on computing (IJOC), 2022
Esther Julien
Krzysztof Postek
cS. .Ilker Birbil
293
5
0
20 Oct 2022
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
On Representing Mixed-Integer Linear Programs by Graph Neural Networks
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
253
24
0
19 Oct 2022
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep
  Reinforcement Learning
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement LearningIEEE Transactions on Computational Social Systems (IEEE TCSS), 2022
Tiantian Chen
Siwen Yan
Jianxiong Guo
Weili Wu
134
46
0
14 Oct 2022
Winner Takes It All: Training Performant RL Populations for
  Combinatorial Optimization
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationNeural Information Processing Systems (NeurIPS), 2022
Nathan Grinsztajn
Daniel Furelos-Blanco
Shikha Surana
Matthew Macfarlane
Thomas D. Barrett
262
50
0
07 Oct 2022
On Representing Linear Programs by Graph Neural Networks
On Representing Linear Programs by Graph Neural NetworksInternational Conference on Learning Representations (ICLR), 2022
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
372
47
0
25 Sep 2022
Deep Attentive Belief Propagation: Integrating Reasoning and Learning
  for Solving Constraint Optimization Problems
Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization ProblemsNeural Information Processing Systems (NeurIPS), 2022
Yanchen Deng
Shufeng Kong
Caihua Liu
Bo An
320
4
0
24 Sep 2022
How Good Is Neural Combinatorial Optimization? A Systematic Evaluation
  on the Traveling Salesman Problem
How Good Is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman ProblemIEEE Computational Intelligence Magazine (IEEE CIM), 2022
Shengcai Liu
Yu Zhang
Shengcai Liu
Xin Yao
239
66
0
22 Sep 2022
Deep-Steiner: Learning to Solve the Euclidean Steiner Tree Problem
Deep-Steiner: Learning to Solve the Euclidean Steiner Tree ProblemInternational Wireless Internet Conference (WICON), 2022
Siqi Wang
Yifan Wang
G. Tong
254
2
0
20 Sep 2022
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent
  Variable Models
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable ModelsAAAI Conference on Artificial Intelligence (AAAI), 2022
Pasquale Minervini
Luca Franceschi
Mathias Niepert
183
14
0
11 Sep 2022
Structured Q-learning For Antibody Design
Structured Q-learning For Antibody Design
Alexander I. Cowen-Rivers
P. Gorinski
Aivar Sootla
Asif R. Khan
Liu Furui
Jun Wang
Jan Peters
H. Ammar
OffRLOnRL
241
5
0
10 Sep 2022
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning
  Enabling Technologies
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling TechnologiesStructural And Multidisciplinary Optimization (SMO), 2022
Adam Thelen
Xiaoge Zhang
Olga Fink
Yan Lu
Sayan Ghosh
B. Youn
Michael D. Todd
S. Mahadevan
Chao Hu
Zhen Hu
SyDaAI4CE
204
274
0
26 Aug 2022
Learning to Prune Instances of Steiner Tree Problem in Graphs
Learning to Prune Instances of Steiner Tree Problem in GraphsInternational Network Optimization Conference (INOC), 2022
Jiwei Zhang
Deepak Ajwani
127
2
0
25 Aug 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization
Self-Supervised Primal-Dual Learning for Constrained OptimizationAAAI Conference on Artificial Intelligence (AAAI), 2022
Seonho Park
Pascal Van Hentenryck
221
70
0
18 Aug 2022
Polynomial Optimization: Enhancing RLT relaxations with Conic
  Constraints
Polynomial Optimization: Enhancing RLT relaxations with Conic Constraints
Brais González-Rodríguez
Raúl Alvite-Pazó
Samuel Alvite-Pazó
Bissan Ghaddar
Julio González-Díaz
77
7
0
11 Aug 2022
Neural Set Function Extensions: Learning with Discrete Functions in High
  Dimensions
Neural Set Function Extensions: Learning with Discrete Functions in High DimensionsNeural Information Processing Systems (NeurIPS), 2022
Nikolaos Karalias
Joshua Robinson
Andreas Loukas
Stefanie Jegelka
360
11
0
08 Aug 2022
Learning with Combinatorial Optimization Layers: a Probabilistic
  Approach
Learning with Combinatorial Optimization Layers: a Probabilistic Approach
Guillaume Dalle
Léo Baty
Louis Bouvier
Axel Parmentier
AI4CE
303
44
0
27 Jul 2022
Branch Ranking for Efficient Mixed-Integer Programming via Offline
  Ranking-based Policy Learning
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning
Zeren Huang
Wenhao Chen
Weinan Zhang
Chuhan Shi
Furui Liu
Hui-Ling Zhen
Mingxuan Yuan
Jianye Hao
Yong Yu
Jun Wang
OffRL
148
2
0
26 Jul 2022
Annealed Training for Combinatorial Optimization on Graphs
Annealed Training for Combinatorial Optimization on Graphs
Haoran Sun
E. Guha
H. Dai
207
25
0
23 Jul 2022
Adaptive Learning for the Resource-Constrained Classification Problem
Adaptive Learning for the Resource-Constrained Classification ProblemEngineering applications of artificial intelligence (EAAI), 2022
Danit Abukasis Shifman
Izack Cohen
Xiaochen Xian
Kejun Huang
G. Singer
92
11
0
19 Jul 2022
Supplementing Recurrent Neural Networks with Annealing to Solve
  Combinatorial Optimization Problems
Supplementing Recurrent Neural Networks with Annealing to Solve Combinatorial Optimization Problems
Shoummo Ahsan Khandoker
Jawaril Munshad Abedin
Mohamed Hibat-Allah
403
11
0
17 Jul 2022
Simulation-guided Beam Search for Neural Combinatorial Optimization
Simulation-guided Beam Search for Neural Combinatorial OptimizationNeural Information Processing Systems (NeurIPS), 2022
Jinho Choo
Yeong-Dae Kwon
Jihoon Kim
Jeongwoo Jae
André Hottung
Kevin Tierney
Youngjune Gwon
383
94
0
13 Jul 2022
Neural Topological Ordering for Computation Graphs
Neural Topological Ordering for Computation GraphsNeural Information Processing Systems (NeurIPS), 2022
Mukul Gagrani
Corrado Rainone
Yang Yang
Harris Teague
Wonseok Jeon
H. V. Hoof
Weizhen Zeng
P. Zappi
Chris Lott
Roberto Bondesan
240
17
0
13 Jul 2022
Learning the Quality of Machine Permutations in Job Shop Scheduling
Learning the Quality of Machine Permutations in Job Shop SchedulingIEEE Access (IEEE Access), 2022
Andrea Corsini
Simone Calderara
M. dell’Amico
137
3
0
07 Jul 2022
Learning to Accelerate Approximate Methods for Solving Integer
  Programming via Early Fixing
Learning to Accelerate Approximate Methods for Solving Integer Programming via Early Fixing
Longkang Li
Baoyuan Wu
200
4
0
05 Jul 2022
Modern graph neural networks do worse than classical greedy algorithms
  in solving combinatorial optimization problems like maximum independent set
Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent setNature Machine Intelligence (Nat. Mach. Intell.), 2022
Maria Chiara Angelini
F. Ricci-Tersenghi
GNNAI4CE
258
43
0
27 Jun 2022
Learning to Control Local Search for Combinatorial Optimization
Learning to Control Local Search for Combinatorial Optimization
Jonas K. Falkner
Daniela Thyssens
Ahmad Bdeir
Lars Schmidt-Thieme
175
20
0
27 Jun 2022
NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search
NAS-Bench-Graph: Benchmarking Graph Neural Architecture SearchNeural Information Processing Systems (NeurIPS), 2022
Yi Qin
Ziwei Zhang
Xin Eric Wang
Zeyang Zhang
Wenwu Zhu
278
35
0
18 Jun 2022
Temporal Multimodal Multivariate Learning
Temporal Multimodal Multivariate LearningKnowledge Discovery and Data Mining (KDD), 2022
Hyoshin Park
Justice Darko
Niharika Deshpande
Venktesh Pandey
Hui Su
M. Ono
Dedrick Barkely
L. Folsom
D. Posselt
Steve Chien
88
11
0
14 Jun 2022
Machine learning-based patient selection in an emergency department
Machine learning-based patient selection in an emergency department
N. Furian
M. O'Sullivan
C. Walker
Melanie Reuter-Oppermann
106
2
0
08 Jun 2022
A Deep Reinforcement Learning Framework For Column Generation
A Deep Reinforcement Learning Framework For Column GenerationNeural Information Processing Systems (NeurIPS), 2022
Cheng Chi
A. Aboussalah
Elias Boutros Khalil
Juyoung Wang
Zoha Sherkat-Masoumi
249
35
0
03 Jun 2022
On the Generalization of Neural Combinatorial Optimization Heuristics
On the Generalization of Neural Combinatorial Optimization Heuristics
S. Manchanda
Sofia Michel
Darko Drakulic
J. Andreoli
236
28
0
01 Jun 2022
Neural Improvement Heuristics for Graph Combinatorial Optimization
  Problems
Neural Improvement Heuristics for Graph Combinatorial Optimization ProblemsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Andoni I. Garmendia
Josu Ceberio
A. Mendiburu
209
7
0
01 Jun 2022
The CLRS Algorithmic Reasoning Benchmark
The CLRS Algorithmic Reasoning BenchmarkInternational Conference on Machine Learning (ICML), 2022
Petar Velivcković
Adria Puigdomenech Badia
David Budden
Razvan Pascanu
Andrea Banino
Mikhail Dashevskiy
R. Hadsell
Charles Blundell
358
109
0
31 May 2022
Reinforcement Learning for Branch-and-Bound Optimisation using
  Retrospective Trajectories
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective TrajectoriesAAAI Conference on Artificial Intelligence (AAAI), 2022
Christopher W. F. Parsonson
Alexandre Laterre
Thomas D. Barrett
286
28
0
28 May 2022
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial SolversAAAI Conference on Artificial Intelligence (AAAI), 2022
Elias Boutros Khalil
Christopher Morris
Andrea Lodi
AI4CE
156
70
0
27 May 2022
Learning to Solve Combinatorial Graph Partitioning Problems via
  Efficient Exploration
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration
Thomas D. Barrett
Christopher W. F. Parsonson
Alexandre Laterre
203
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DOGE-Train: Discrete Optimization on GPU with End-to-end Training
DOGE-Train: Discrete Optimization on GPU with End-to-end TrainingAAAI Conference on Artificial Intelligence (AAAI), 2022
Ahmed Abbas
Paul Swoboda
260
6
0
23 May 2022
Learning to branch with Tree MDPs
Learning to branch with Tree MDPsNeural Information Processing Systems (NeurIPS), 2022
Lara Scavuzzo
F. Chen
Didier Chételat
Maxime Gasse
Andrea Lodi
Neil Yorke-Smith
K. Aardal
AI4CE
294
71
0
23 May 2022
Machine Learning for Combinatorial Optimisation of Partially-Specified
  Problems: Regret Minimisation as a Unifying Lens
Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens
Stefano Teso
Laurens Bliek
Andrea Borghesi
M. Lombardi
Neil Yorke-Smith
Tias Guns
Baptiste Caramiaux
187
3
0
20 May 2022
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