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Exact Combinatorial Optimization with Graph Convolutional Neural
  Networks

Exact Combinatorial Optimization with Graph Convolutional Neural Networks

4 June 2019
Maxime Gasse
Didier Chételat
Nicola Ferroni
Laurent Charlin
Andrea Lodi
    GNN
    CML
ArXivPDFHTML

Papers citing "Exact Combinatorial Optimization with Graph Convolutional Neural Networks"

50 / 228 papers shown
Title
Learning To Dive In Branch And Bound
Learning To Dive In Branch And Bound
Max B. Paulus
Andreas Krause
29
4
0
24 Jan 2023
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
Hao Wang
Pan Li
13
14
0
08 Jan 2023
Learning a Generic Value-Selection Heuristic Inside a Constraint
  Programming Solver
Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver
Tom Marty
Tristan François
Pierre Tessier
Louis Gautier
Louis-Martin Rousseau
Quentin Cappart
40
7
0
05 Jan 2023
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Machine Learning for Large-Scale Optimization in 6G Wireless Networks
Yandong Shi
Lixiang Lian
Yuanming Shi
Zixin Wang
Yong Zhou
Liqun Fu
Lin Bai
Jun Zhang
Wei Zhang
AI4CE
39
76
0
03 Jan 2023
A machine learning framework for neighbor generation in metaheuristic
  search
A machine learning framework for neighbor generation in metaheuristic search
De-You Liu
Vincent Perreault
A. Hertz
Andrea Lodi
9
7
0
22 Dec 2022
Local Branching Relaxation Heuristics for Integer Linear Programs
Local Branching Relaxation Heuristics for Integer Linear Programs
Taoan Huang
Aaron Ferber
Yuandong Tian
B. Dilkina
Benoit Steiner
15
3
0
15 Dec 2022
Learning to repeatedly solve routing problems
Learning to repeatedly solve routing problems
Mouad Morabit
G. Desaulniers
Andrea Lodi
17
3
0
15 Dec 2022
Learning on Graphs for Mineral Asset Valuation Under Supply and Demand
  Uncertainty
Learning on Graphs for Mineral Asset Valuation Under Supply and Demand Uncertainty
Yassine Yaakoubi
Hager Radi
R. Dimitrakopoulos
17
0
0
07 Dec 2022
Solving Bilevel Knapsack Problem using Graph Neural Networks
Solving Bilevel Knapsack Problem using Graph Neural Networks
S. Kwon
Hwayong Choi
Sungsoo Park
19
3
0
24 Nov 2022
UNSAT Solver Synthesis via Monte Carlo Forest Search
UNSAT Solver Synthesis via Monte Carlo Forest Search
Chris Cameron
Jason S. Hartford
Taylor Lundy
T. Truong
Alan Milligan
Rex Chen
Kevin Leyton-Brown
21
1
0
22 Nov 2022
Learning context-aware adaptive solvers to accelerate quadratic
  programming
Learning context-aware adaptive solvers to accelerate quadratic programming
Haewon Jung
Junyoung Park
Jinkyoo Park
17
6
0
22 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 Learning
Longkang Li
Siyuan Liang
Zihao Zhu
Chris H. Q. Ding
Hong Zha
Baoyuan Wu
AI4CE
7
7
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 Networks
Abdel Ghani Labassi
Didier Chételat
Andrea Lodi
24
31
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 Location
Shiqing Liu
Xueming Yan
Yaochu Jin
37
9
0
27 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
29
16
0
19 Oct 2022
Learning Universe Model for Partial Matching Networks over Multiple
  Graphs
Learning Universe Model for Partial Matching Networks over Multiple Graphs
Zetian Jiang
Jiaxin Lu
Tianzhe Wang
Junchi Yan
24
2
0
19 Oct 2022
Travel the Same Path: A Novel TSP Solving Strategy
Travel the Same Path: A Novel TSP Solving Strategy
Pin Hu
9
0
0
12 Oct 2022
On Representing Linear Programs by Graph Neural Networks
On Representing Linear Programs by Graph Neural Networks
Ziang Chen
Jialin Liu
Xinshang Wang
Jian Lu
W. Yin
AI4CE
60
31
0
25 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
OffRL
OnRL
24
3
0
10 Sep 2022
Lifelong Learning for Neural powered Mixed Integer Programming
Lifelong Learning for Neural powered Mixed Integer Programming
S. Manchanda
Sayan Ranu
CLL
25
1
0
24 Aug 2022
One Model, Any CSP: Graph Neural Networks as Fast Global Search
  Heuristics for Constraint Satisfaction
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction
Jan Tonshoff
Berke Kisin
Jakob Lindner
Martin Grohe
GNN
18
22
0
22 Aug 2022
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
Neuro-Symbolic Learning: Principles and Applications in Ophthalmology
Muhammad Hassan
Haifei Guan
Aikaterini Melliou
Yuqi Wang
Qianhui Sun
...
Qi Huang
Jiefu Tan
Qinwang Xing
Peiwu Qin
Dongmei Yu
NAI
36
14
0
31 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
M. Yuan
Jianye Hao
Yong Yu
Jun Wang
OffRL
16
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
22
18
0
23 Jul 2022
Unsupervised Learning for Combinatorial Optimization with Principled
  Objective Relaxation
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Haoyu Wang
Nan Wu
Hang Yang
Cong Hao
Pan Li
29
29
0
13 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
16
3
0
05 Jul 2022
Lookback for Learning to Branch
Lookback for Learning to Branch
Prateek Gupta
Elias Boutros Khalil
Didier Chételat
Maxime Gasse
Yoshua Bengio
Andrea Lodi
M. P. Kumar
10
27
0
30 Jun 2022
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation
  Learning
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning
Max B. Paulus
Giulia Zarpellon
Andreas Krause
Laurent Charlin
Chris J. Maddison
25
57
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
30
18
0
27 Jun 2022
Affinity-Aware Graph Networks
Affinity-Aware Graph Networks
A. Velingker
A. Sinop
Ira Ktena
Petar Velickovic
Sreenivas Gollapudi
GNN
50
16
0
23 Jun 2022
Deep Reinforcement Learning for Exact Combinatorial Optimization:
  Learning to Branch
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch
Tianyu Zhang
Amin Banitalebi-Dehkordi
Yong Zhang
BDL
OffRL
8
14
0
14 Jun 2022
Optimal Solutions for Joint Beamforming and Antenna Selection: From
  Branch and Bound to Graph Neural Imitation Learning
Optimal Solutions for Joint Beamforming and Antenna Selection: From Branch and Bound to Graph Neural Imitation Learning
S. Shrestha
Xiao Fu
Mingyi Hong
6
13
0
11 Jun 2022
Grid-SiPhyR: An end-to-end learning to optimize framework for
  combinatorial problems in power systems
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems
R. Haider
Anuradha M. Annaswamy
23
2
0
11 Jun 2022
A Deep Reinforcement Learning Framework For Column Generation
A Deep Reinforcement Learning Framework For Column Generation
Cheng Chi
A. Aboussalah
Elias Boutros Khalil
Juyoung Wang
Zoha Sherkat-Masoumi
13
26
0
03 Jun 2022
Reinforcement Learning for Branch-and-Bound Optimisation using
  Retrospective Trajectories
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectories
Christopher W. F. Parsonson
Alexandre Laterre
Thomas D. Barrett
17
19
0
28 May 2022
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers
Elias Boutros Khalil
Christopher Morris
Andrea Lodi
AI4CE
31
48
0
27 May 2022
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
DOGE-Train: Discrete Optimization on GPU with End-to-end Training
Ahmed Abbas
Paul Swoboda
38
6
0
23 May 2022
Learning to branch with Tree MDPs
Learning to branch with Tree MDPs
Lara Scavuzzo
F. Chen
Didier Chételat
Maxime Gasse
Andrea Lodi
Neil Yorke-Smith
K. Aardal
AI4CE
35
51
0
23 May 2022
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale
  Combinatorial Optimisation
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
David Ireland
Giovanni Montana
GNN
6
10
0
20 May 2022
Neural Combinatorial Optimization: a New Player in the Field
Neural Combinatorial Optimization: a New Player in the Field
Andoni I. Garmendia
Josu Ceberio
A. Mendiburu
24
11
0
03 May 2022
Learning for Spatial Branching: An Algorithm Selection Approach
Learning for Spatial Branching: An Algorithm Selection Approach
Bissan Ghaddar
Ignacio Gómez-Casares
Julio González-Díaz
Brais González-Rodríguez
Beatriz Pateiro-López
Sofía Rodríguez-Ballesteros
13
12
0
22 Apr 2022
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted
  Graph Convolutional Neural Networks
Learning to solve Minimum Cost Multicuts efficiently using Edge-Weighted Graph Convolutional Neural Networks
Steffen Jung
M. Keuper
GNN
14
3
0
04 Apr 2022
Pareto Set Learning for Neural Multi-objective Combinatorial
  Optimization
Pareto Set Learning for Neural Multi-objective Combinatorial Optimization
Xi Lin
Zhiyuan Yang
Qingfu Zhang
20
62
0
29 Mar 2022
Solving Disjunctive Temporal Networks with Uncertainty under Restricted
  Time-Based Controllability using Tree Search and Graph Neural Networks
Solving Disjunctive Temporal Networks with Uncertainty under Restricted Time-Based Controllability using Tree Search and Graph Neural Networks
Kevin Osanlou
J. Frank
Andrei Bursuc
Tristan Cazenave
Éric Jacopin
Christophe Guettier
J. Benton
AI4CE
17
2
0
28 Mar 2022
A Survey for Solving Mixed Integer Programming via Machine Learning
A Survey for Solving Mixed Integer Programming via Machine Learning
Jiayi Zhang
Chang-rui Liu
Junchi Yan
Xijun Li
Hui-Ling Zhen
M. Yuan
AI4CE
32
72
0
06 Mar 2022
The Machine Learning for Combinatorial Optimization Competition (ML4CO):
  Results and Insights
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Maxime Gasse
Quentin Cappart
J. Charfreitag
Laurent Charlin
Didier Chételat
...
He Minggui
Hao Hao
Zhang Zhiyu
An Zhiwu
M. Kun
21
30
0
04 Mar 2022
Neural Simulated Annealing
Neural Simulated Annealing
Alvaro H. C. Correia
Daniel E. Worrall
Roberto Bondesan
11
7
0
04 Mar 2022
Learning to Schedule Heuristics for the Simultaneous Stochastic
  Optimization of Mining Complexes
Learning to Schedule Heuristics for the Simultaneous Stochastic Optimization of Mining Complexes
Yassine Yaakoubi
R. Dimitrakopoulos
27
10
0
25 Feb 2022
Reinforcement Learning in Practice: Opportunities and Challenges
Reinforcement Learning in Practice: Opportunities and Challenges
Yuxi Li
OffRL
36
9
0
23 Feb 2022
Adaptive Cut Selection in Mixed-Integer Linear Programming
Adaptive Cut Selection in Mixed-Integer Linear Programming
Mark Turner
Thorsten Koch
Felipe Serrano
Michael Winkler
52
32
0
22 Feb 2022
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