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Learning to Branch

27 March 2018

Papers citing "Learning to Branch"

49 / 99 papers shown

Title
(Machine) Learning to Improve the Empirical Performance of Discrete Algorithms Imran Adham J. D. Loera Zhenyang Zhang 59 4 0 29 Sep 2021
Learning-to-learn non-convex piecewise-Lipschitz functions Maria-Florina Balcan M. Khodak Dravyansh Sharma Ameet Talwalkar 69 14 0 19 Aug 2021
Accelerating Quadratic Optimization with Reinforcement Learning Jeffrey Ichnowski Paras Jain Bartolomeo Stellato G. Banjac Michael Luo Francesco Borrelli Joseph E. Gonzalez Ion Stoica Ken Goldberg OffRL 85 36 0 22 Jul 2021
Faster Matchings via Learned Duals M. Dinitz Sungjin Im Thomas Lavastida Benjamin Moseley Sergei Vassilvitskii 51 69 0 20 Jul 2021
Learning-based Support Estimation in Sublinear Time T. Eden Piotr Indyk Shyam Narayanan R. Rubinfeld Sandeep Silwal Tal Wagner 73 28 0 15 Jun 2021
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond Maria-Florina Balcan Siddharth Prasad Tuomas Sandholm Ellen Vitercik 57 39 0 08 Jun 2021
Learning Hard Optimization Problems: A Data Generation Perspective James Kotary Ferdinando Fioretto Pascal Van Hentenryck 41 38 0 04 Jun 2021
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 109 71 0 28 May 2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints Anselm Paulus Michal Rolínek Vít Musil Brandon Amos Georg Martius 82 62 0 05 May 2021
Statistically-Robust Clustering Techniques for Mapping Spatial Hotspots: A Survey Yiqun Xie Shashi Shekhar Yan Li 77 36 0 22 Mar 2021
Data driven semi-supervised learning Maria-Florina Balcan Dravyansh Sharma 76 16 0 18 Mar 2021
Learning to Schedule Heuristics in Branch-and-Bound Antonia Chmiela Elias Boutros Khalil Ambros M. Gleixner Andrea Lodi Sebastian Pokutta 97 62 0 18 Mar 2021
Generalization in portfolio-based algorithm selection Maria-Florina Balcan Tuomas Sandholm Ellen Vitercik 76 12 0 24 Dec 2020
Solving Mixed Integer Programs Using Neural Networks Vinod Nair Sergey Bartunov Felix Gimeno Ingrid von Glehn Pawel Lichocki ... Pushmeet Kohli Ira Ktena Yujia Li Oriol Vinyals Yori Zwols 216 251 0 23 Dec 2020
Learnable and Instance-Robust Predictions for Online Matching, Flows and Load Balancing Thomas Lavastida Benjamin Moseley R. Ravi Chenyang Xu OOD 104 59 0 23 Nov 2020
Data-driven Algorithm Design Maria-Florina Balcan 37 2 0 14 Nov 2020
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers Antoine Prouvost Justin Dumouchelle Lara Scavuzzo Maxime Gasse Didier Chételat Andrea Lodi OffRL 106 49 0 11 Nov 2020
Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online Algorithms Alexander Wei Fred Zhang 93 99 0 22 Oct 2020
A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing Ping Lang Xiongjun Fu M. Martorella Jian Dong Rui Qin Xianpeng Meng M. Xie 41 42 0 29 Sep 2020
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning Yuan Sun Sheng Wang Yunzhuang Shen Xiaodong Li Andreas T. Ernst M. Kirley 63 28 0 29 Jul 2020
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme Dimitris Bertsimas V. Digalakis 61 5 0 17 Jul 2020
Learning Branching Heuristics for Propositional Model Counting Pashootan Vaezipoor Gil Lederman Yuhuai Wu Chris J. Maddison Roger C. Grosse Sanjit A. Seshia F. Bacchus LRM 82 13 0 07 Jul 2020
Learning Combined Set Covering and Traveling Salesman Problem Yuwen Yang J. Rajgopal 31 4 0 07 Jul 2020
Curriculum learning for multilevel budgeted combinatorial problems Adel Nabli Margarida Carvalho AI4CE 85 4 0 07 Jul 2020
Guarantees for Tuning the Step Size using a Learning-to-Learn Approach Xiang Wang Shuai Yuan Chenwei Wu Rong Ge 75 16 0 30 Jun 2020
Refined bounds for algorithm configuration: The knife-edge of dual class approximability Maria-Florina Balcan Tuomas Sandholm Ellen Vitercik 71 15 0 21 Jun 2020
Online Page Migration with ML Advice Piotr Indyk Frederik Mallmann-Trenn Slobodan Mitrović R. Rubinfeld OnRL 124 18 0 09 Jun 2020
Reinforcement Learning for Variable Selection in a Branch and Bound Algorithm Marc Etheve Zacharie Alès Côme Bissuel Olivier Juan S. Kedad-Sidhoum 68 39 0 20 May 2020
A General Large Neighborhood Search Framework for Solving Integer Linear Programs Jialin Song Ravi Lanka Yisong Yue B. Dilkina 118 22 0 29 Mar 2020
Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers Michal Rolínek Paul Swoboda Dominik Zietlow Anselm Paulus Vít Musil Georg Martius 90 113 0 25 Mar 2020
Learning Complexity of Simulated Annealing Avrim Blum Chen Dan Saeed Seddighin 245 19 0 06 Mar 2020
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies Giulia Zarpellon Jason Jo Andrea Lodi Yoshua Bengio 93 98 0 12 Feb 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 106 57 0 01 Jan 2020
Learning-Based Low-Rank Approximations Piotr Indyk A. Vakilian Yang Yuan 94 69 0 30 Oct 2019
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 76 35 0 08 Aug 2019
MIPaaL: Mixed Integer Program as a Layer Aaron Ferber Bryan Wilder B. Dilkina Milind Tambe 105 147 0 12 Jul 2019
Learning to Handle Parameter Perturbations in Combinatorial Optimization: an Application to Facility Location Andrea Lodi Luca Mossina Emmanuel Rachelson 54 30 0 12 Jul 2019
Learning to Link Maria-Florina Balcan Travis Dick Manuel Lang 90 25 0 01 Jul 2019
Reinforcement Learning for Integer Programming: Learning to Cut Yunhao Tang Shipra Agrawal Yuri Faenza AI4CE 103 174 0 11 Jun 2019
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing J. D. Loera Jamie Haddock A. Ma Deanna Needell 22 0 0 31 May 2019
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees Maria-Florina Balcan Tuomas Sandholm Ellen Vitercik 70 16 0 26 May 2019
Learning to Prune: Speeding up Repeated Computations Daniel Alabi Adam Tauman Kalai Katrina Ligett Cameron Musco Christos Tzamos Ellen Vitercik 41 19 0 26 Apr 2019
Semi-bandit Optimization in the Dispersed Setting Maria-Florina Balcan Travis Dick W. Pegden 50 21 0 18 Apr 2019
Empirical Bayes Regret Minimization Chih-Wei Hsu Branislav Kveton Ofer Meshi Martin Mladenov Csaba Szepesvári 77 13 0 04 Apr 2019
Guiding High-Performance SAT Solvers with Unsat-Core Predictions Daniel Selsam Nikolaj S. Bjørner NAI 103 122 0 12 Mar 2019
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration Robert D. Kleinberg Kevin Leyton-Brown Brendan Lucier Devon R. Graham 53 20 0 14 Feb 2019
Learning Space Partitions for Nearest Neighbor Search Yihe Dong Piotr Indyk Ilya P. Razenshteyn Tal Wagner 86 12 0 24 Jan 2019
LORM: Learning to Optimize for Resource Management in Wireless Networks with Few Training Samples Yifei Shen Yuanming Shi Jun Zhang Khaled B. Letaief 19 6 0 18 Dec 2018
Small Sample Learning in Big Data Era Jun Shu Zongben Xu Deyu Meng 101 72 0 14 Aug 2018