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From Large to Small Datasets: Size Generalization for Clustering Algorithm Selection
Vaggos Chatziafratis, Ishani Karmarkar, and Ellen Vitercik
Preprint
[paper] [slides] [video] -
Bandit Profit Maximization for Targeted Marketing
Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy
Preprint
[paper] -
New Sequence-Independent Lifting Techniques for Cutting Planes and When They Induce Facets
Siddharth Prasad, Ellen Vitercik, Maria-Florina Balcan, and Tuomas Sandholm
Preprint
[paper] -
Sorting from Crowdsourced Comparisons using Expert Verifications
Ellen Vitercik, Manolis Zampetakis, and David Zhang
Preprint
[paper] -
Algorithmic Contract Design for Crowdsourced Ranking
Kiriaki Frangias, Andrew Lin, Ellen Vitercik, and Manolis Zampetakis
Preprint
[paper] -
Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization
Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, and Ellen Vitercik
Journal of the ACM (JACM), 2024
Supersedes the ICML’20 and ICML’18 papers below
[paper] -
Generalization Guarantees for Multi-Item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
To appear in Operations Research (OR)
Supersedes the EC’18 paper below
[paper] -
Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
Wenshuo Guo, Nika Haghtalab, Kirthevasan Kandasamy, and Ellen Vitercik
ACM Conference on Economics and Computation (EC) 2023
🏆 Exemplary Artificial Intelligence Track Paper Award (EC 2023)
[paper] [slides] [video] -
Disincentivizing Polarization in Social Networks
Christian Borgs, Jennifer Chayes, Christian Ikeokwu, and Ellen Vitercik
ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO) 2023
[paper] -
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, and Ellen Vitercik
Conference on Neural Information Processing Systems (NeurIPS) 2022
[paper] -
No-Regret Learning in Partially-Informed Auctions
Wenshuo Guo, Michael I. Jordan, and Ellen Vitercik
International Conference on Machine Learning (ICML) 2022
[paper] -
Improved Sample Complexity Bounds for Branch-and-Cut
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, and Ellen Vitercik
International Conference on Principles and Practice of Constraint Programming (CP) 2022
[paper] -
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, and Ellen Vitercik
Conference on Neural Information Processing Systems (NeurIPS) 2021
[paper] [slides] [poster] -
Revenue Maximization via Machine Learning with Noisy Data
Ellen Vitercik and Tom Yan
Conference on Neural Information Processing Systems (NeurIPS) 2021
[paper] -
How Much Data Is Sufficient to Learn High-performing Algorithms? Generalization Guarantees for Data-driven Algorithm Design
Maria-Florina Balcan, Dan DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm, and Ellen Vitercik
ACM Symposium on Theory of Computing (STOC) 2021
[STOC] [arXiv] [slides] [video] [poster] -
Private Optimization Without Constraint Violations
Andrés Muñoz Medina, Umar Syed, Sergei Vassilvitskii, and Ellen Vitercik
International Conference on Artificial Intelligence and Statistics (AISTATS) 2021
[paper] [slides] [poster] -
Generalization in Portfolio-based Algorithm Selection
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
AAAI Conference on Artificial Intelligence 2021
[paper] [slides] [poster] -
Refined Bounds for Algorithm Configuration: The Knife-Edge of Dual Class Approximability
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
International Conference on Machine Learning (ICML) 2020
[paper] [slides] [video] -
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
AAAI Conference on Artificial Intelligence 2020
[paper] [poster] -
Estimating Approximate Incentive Compatibility
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
ACM Conference on Economics and Computation (EC) 2019
🏆 Exemplary Artificial Intelligence Track Paper Award (EC 2019)
🏆 Best Presentation by a Student or Postdoctoral Researcher (EC 2019)
[paper] [slides] [video] [poster] -
Learning to Prune: Speeding up Repeated Computations
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, and Ellen Vitercik
Conference on Learning Theory (COLT) 2019
[paper] [slides] [video] [poster] -
Algorithmic Greenlining: An Approach to Increase Diversity
Christian Borgs, Jennifer Chayes, Nika Haghtalab, Adam Tauman Kalai, and Ellen Vitercik
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) 2019
[paper] [slides] [poster] -
Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization
Maria-Florina Balcan, Travis Dick, and Ellen Vitercik
IEEE Symposium on Foundations of Computer Science (FOCS) 2018
[paper] [slides] [poster] -
Learning to Branch
Maria-Florina Balcan, Travis Dick, Tuomas Sandholm, and Ellen Vitercik
International Conference on Machine Learning (ICML) 2018
[paper] [slides] [video] -
A General Theory of Sample Complexity for Multi-Item Profit Maximization
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
ACM Conference on Economics and Computation (EC) 2018
[paper] [slides] [video] -
Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions
Bernhard Haeupler, Amirbehshad Shahrasbi, and Ellen Vitercik
International Colloquium on Automata, Languages and Programming (ICALP) 2018
[paper] -
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, and Colin White
Conference on Learning Theory (COLT) 2017
[paper] [slides] -
Sample Complexity of Automated Mechanism Design
Maria-Florina Balcan, Tuomas Sandholm, and Ellen Vitercik
Conference on Neural Information Processing Systems (NeurIPS) 2016
[paper] [slides] [video] -
Learning Combinatorial Functions from Pairwise Comparisons
Maria-Florina Balcan, Ellen Vitercik, and Colin White
Conference on Learning Theory (COLT) 2016
[paper]