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Improved Sample Complexity Bounds for Branch-and-Cut

Improved Sample Complexity Bounds for Branch-and-Cut

18 November 2021
Maria-Florina Balcan
Siddharth Prasad
Tuomas Sandholm
Ellen Vitercik
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Papers citing "Improved Sample Complexity Bounds for Branch-and-Cut"

16 / 16 papers shown
Title
Sample Complexity of Tree Search Configuration: Cutting Planes and
  Beyond
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Maria-Florina Balcan
Siddharth Prasad
Tuomas Sandholm
Ellen Vitercik
9
37
0
08 Jun 2021
Learning to Select Cuts for Efficient Mixed-Integer Programming
Learning to Select Cuts for Efficient Mixed-Integer Programming
Zeren Huang
Kerong Wang
Furui Liu
Hui-Ling Zhen
Weinan Zhang
Mingxuan Yuan
Jianye Hao
Yong Yu
Jun Wang
43
68
0
28 May 2021
Learning to Schedule Heuristics in Branch-and-Bound
Learning to Schedule Heuristics in Branch-and-Bound
Antonia Chmiela
Elias Boutros Khalil
Ambros M. Gleixner
Andrea Lodi
Sebastian Pokutta
50
60
0
18 Mar 2021
Hybrid Models for Learning to Branch
Hybrid Models for Learning to Branch
Prateek Gupta
Maxime Gasse
Elias Boutros Khalil
M. P. Kumar
Andrea Lodi
Yoshua Bengio
GNN
117
126
0
26 Jun 2020
A General Large Neighborhood Search Framework for Solving Integer Linear
  Programs
A General Large Neighborhood Search Framework for Solving Integer Linear Programs
Jialin Song
Ravi Lanka
Yisong Yue
B. Dilkina
49
20
0
29 Mar 2020
How much data is sufficient to learn high-performing algorithms?
  Generalization guarantees for data-driven algorithm design
How much data is sufficient to learn high-performing algorithms? Generalization guarantees for data-driven algorithm design
Maria-Florina Balcan
Dan F. DeBlasio
Travis Dick
Carl Kingsford
Tuomas Sandholm
Ellen Vitercik
28
34
0
08 Aug 2019
Reinforcement Learning for Integer Programming: Learning to Cut
Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang
Shipra Agrawal
Yuri Faenza
AI4CE
26
170
0
11 Jun 2019
Exact Combinatorial Optimization with Graph Convolutional Neural
  Networks
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime Gasse
Didier Chételat
Nicola Ferroni
Laurent Charlin
Andrea Lodi
GNN
CML
82
481
0
04 Jun 2019
LeapsAndBounds: A Method for Approximately Optimal Algorithm
  Configuration
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Gellert Weisz
András Gyorgy
Csaba Szepesvári
13
35
0
02 Jul 2018
Learning to Branch
Learning to Branch
Maria-Florina Balcan
Travis Dick
Tuomas Sandholm
Ellen Vitercik
25
172
0
27 Mar 2018
Learning-Theoretic Foundations of Algorithm Configuration for
  Combinatorial Partitioning Problems
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
Maria-Florina Balcan
Vaishnavh Nagarajan
Ellen Vitercik
Colin White
34
60
0
14 Nov 2016
A PAC Approach to Application-Specific Algorithm Selection
A PAC Approach to Application-Specific Algorithm Selection
Rishi Gupta
Tim Roughgarden
41
116
0
23 Nov 2015
ParamILS: An Automatic Algorithm Configuration Framework
ParamILS: An Automatic Algorithm Configuration Framework
Frank Hutter
Thomas Stuetzle
Kevin Leyton-Brown
T. Stützle
61
1,066
0
15 Jan 2014
DASH: Dynamic Approach for Switching Heuristics
DASH: Dynamic Approach for Switching Heuristics
G. D. Liberto
Serdar Kadioğlu
Kevin Leo
Y. Malitsky
40
58
0
17 Jul 2013
A Bayesian Approach to Tackling Hard Computational Problems
A Bayesian Approach to Tackling Hard Computational Problems
Eric Horvitz
Yongshao Ruan
Carla P. Gomes
Henry A. Kautz
B. Selman
D. M. Chickering
54
149
0
10 Jan 2013
SATzilla: Portfolio-based Algorithm Selection for SAT
SATzilla: Portfolio-based Algorithm Selection for SAT
Lin Xu
Frank Hutter
Holger H. Hoos
Kevin Leyton-Brown
75
969
0
31 Oct 2011
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