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Sample Complexity of Tree Search Configuration: Cutting Planes and
  Beyond

Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond

8 June 2021
Maria-Florina Balcan
Siddharth Prasad
Tuomas Sandholm
Ellen Vitercik
ArXivPDFHTML

Papers citing "Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond"

16 / 16 papers shown
Title
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
54
70
0
28 May 2021
Data-driven Algorithm Design
Data-driven Algorithm Design
Maria-Florina Balcan
19
2
0
14 Nov 2020
Refined bounds for algorithm configuration: The knife-edge of dual class
  approximability
Refined bounds for algorithm configuration: The knife-edge of dual class approximability
Maria-Florina Balcan
Tuomas Sandholm
Ellen Vitercik
20
15
0
21 Jun 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
45
35
0
08 Aug 2019
MIPaaL: Mixed Integer Program as a Layer
MIPaaL: Mixed Integer Program as a Layer
Aaron Ferber
Bryan Wilder
B. Dilkina
Milind Tambe
49
145
0
12 Jul 2019
Reinforcement Learning for Integer Programming: Learning to Cut
Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang
Shipra Agrawal
Yuri Faenza
AI4CE
55
171
0
11 Jun 2019
Learning to Optimize Computational Resources: Frugal Training with
  Generalization Guarantees
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees
Maria-Florina Balcan
Tuomas Sandholm
Ellen Vitercik
31
16
0
26 May 2019
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive
  Algorithm Configuration
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration
Robert D. Kleinberg
Kevin Leyton-Brown
Brendan Lucier
Devon R. Graham
30
20
0
14 Feb 2019
Machine Learning for Combinatorial Optimization: a Methodological Tour
  d'Horizon
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon
Yoshua Bengio
Andrea Lodi
Antoine Prouvost
153
1,377
0
15 Nov 2018
LeapsAndBounds: A Method for Approximately Optimal Algorithm
  Configuration
LeapsAndBounds: A Method for Approximately Optimal Algorithm Configuration
Gellert Weisz
András Gyorgy
Csaba Szepesvári
35
35
0
02 Jul 2018
Learning Robust Search Strategies Using a Bandit-Based Approach
Learning Robust Search Strategies Using a Bandit-Based Approach
Wei Xia
R. Yap
28
32
0
10 May 2018
Learning to Branch
Learning to Branch
Maria-Florina Balcan
Travis Dick
Tuomas Sandholm
Ellen Vitercik
48
173
0
27 Mar 2018
A PAC Approach to Application-Specific Algorithm Selection
A PAC Approach to Application-Specific Algorithm Selection
Rishi Gupta
Tim Roughgarden
55
117
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
80
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
62
58
0
17 Jul 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
98
975
0
31 Oct 2011
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