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Improving Optimization Bounds using Machine Learning: Decision Diagrams
  meet Deep Reinforcement Learning

Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning

10 September 2018
Quentin Cappart
Emmanuel Goutierre
David Bergman
Louis-Martin Rousseau
    AI4CE
ArXivPDFHTML

Papers citing "Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning"

11 / 11 papers shown
Title
Conformal Prediction with Upper and Lower Bound Models
Miao Li
Michael Klamkin
Mathieu Tanneau
Reza Zandehshahvar
Pascal Van Hentenryck
50
0
0
06 Mar 2025
LEO: Learning Efficient Orderings for Multiobjective Binary Decision
  Diagrams
LEO: Learning Efficient Orderings for Multiobjective Binary Decision Diagrams
R. Patel
Elias Boutros Khalil
39
0
0
06 Jul 2023
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
Deployment Optimization for Shared e-Mobility Systems with Multi-agent
  Deep Neural Search
Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search
Man Luo
Bowen Du
Konstantin Klemmer
Hongming Zhu
Hongkai Wen
23
5
0
03 Nov 2021
Combinatorial optimization and reasoning with graph neural networks
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart
Didier Chételat
Elias Boutros Khalil
Andrea Lodi
Christopher Morris
Petar Velickovic
AI4CE
32
348
0
18 Feb 2021
Curriculum learning for multilevel budgeted combinatorial problems
Curriculum learning for multilevel budgeted combinatorial problems
Adel Nabli
Margarida Carvalho
AI4CE
11
4
0
07 Jul 2020
Learning Objective Boundaries for Constraint Optimization Problems
Learning Objective Boundaries for Constraint Optimization Problems
Helge Spieker
A. Gotlieb
25
3
0
20 Jun 2020
Learning to Solve Combinatorial Optimization Problems on Real-World
  Graphs in Linear Time
Learning to Solve Combinatorial Optimization Problems on Real-World Graphs in Linear Time
Iddo Drori
Anant Kharkar
William R. Sickinger
Brandon Kates
Qiang Ma
Suwen Ge
Eden Dolev
Brenda L Dietrich
David P. Williamson
Madeleine Udell
22
82
0
06 Jun 2020
Combining Reinforcement Learning and Constraint Programming for
  Combinatorial Optimization
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization
Quentin Cappart
Thierry Moisan
Louis-Martin Rousseau
Isabeau Prémont-Schwarz
A. Ciré
26
138
0
02 Jun 2020
Lossless Compression of Deep Neural Networks
Lossless Compression of Deep Neural Networks
Thiago Serra
Abhinav Kumar
Srikumar Ramalingam
24
56
0
01 Jan 2020
How to Evaluate Machine Learning Approaches for Combinatorial
  Optimization: Application to the Travelling Salesman Problem
How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman Problem
Antoine François
Quentin Cappart
Louis-Martin Rousseau
22
13
0
28 Sep 2019
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