Journal publications

• Generalization Guarantees for Multi-Item Profit Maximization: Pricing, Auctions, and Randomized Mechanisms
  with Maria-Florina Balcan and Tuomas Sandholm
  To appear in Operations Research (OR)
  Supersedes the EC’18 paper below

Conference publications

• Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty
  with Wenshuo Guo, Nika Haghtalab, and Kirthevasan Kandasamy
  ACM Conference on Economics and Computation (EC) 2023
  🏆 Exemplary Artificial Intelligence Track Paper Award (EC 2023)
  [paper] [slides] [video]

• Disincentivizing Polarization in Social Networks
  with Christian Borgs, Jennifer Chayes, and Christian Ikeokwu
  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
  with Maria-Florina Balcan, Siddharth Prasad, and Tuomas Sandholm
  Conference on Neural Information Processing Systems (NeurIPS) 2022
  [paper]

• No-Regret Learning in Partially-Informed Auctions
  with Wenshuo Guo and Michael I. Jordan
  International Conference on Machine Learning (ICML) 2022
  [paper]

• Improved Sample Complexity Bounds for Branch-and-Cut
  with Maria-Florina Balcan, Siddharth Prasad, and Tuomas Sandholm
  International Conference on Principles and Practice of Constraint Programming (CP) 2022
  [paper]

• Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
  with Maria-Florina Balcan, Siddharth Prasad, and Tuomas Sandholm
  Conference on Neural Information Processing Systems (NeurIPS) 2021
  [paper] [slides] [poster]

• Revenue Maximization via Machine Learning with Noisy Data
  with 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
  with Maria-Florina Balcan, Dan DeBlasio, Travis Dick, Carl Kingsford, and Tuomas Sandholm
  ACM Symposium on Theory of Computing (STOC) 2021
  [STOC] [arXiv] [slides] [video] [poster]

• Private Optimization Without Constraint Violations
  with Andrés Muñoz Medina, Umar Syed, and Sergei Vassilvitskii
  International Conference on Artificial Intelligence and Statistics (AISTATS) 2021
  [paper] [slides] [poster]

• Generalization in Portfolio-based Algorithm Selection
  with Maria-Florina Balcan and Tuomas Sandholm
  AAAI Conference on Artificial Intelligence 2021
  [paper] [slides] [poster]

• Refined Bounds for Algorithm Configuration: The Knife-Edge of Dual Class Approximability
  with Maria-Florina Balcan and Tuomas Sandholm
  International Conference on Machine Learning (ICML) 2020
  [paper] [slides] [video]

• Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees
  with Maria-Florina Balcan and Tuomas Sandholm
  AAAI Conference on Artificial Intelligence 2020
  [paper] [poster]

• Estimating Approximate Incentive Compatibility
  with Maria-Florina Balcan and Tuomas Sandholm
  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
  with Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, and Christos Tzamos
  Conference on Learning Theory (COLT) 2019
  [paper] [slides] [video] [poster]

• Algorithmic Greenlining: An Approach to Increase Diversity
  with Christian Borgs, Jennifer Chayes, Nika Haghtalab, and Adam Tauman Kalai
  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
  with Maria-Florina Balcan and Travis Dick
  IEEE Symposium on Foundations of Computer Science (FOCS) 2018
  [paper] [slides] [poster]

• Learning to Branch
  with Maria-Florina Balcan, Travis Dick, and Tuomas Sandholm
  International Conference on Machine Learning (ICML) 2018
  [paper] [slides] [video]

• A General Theory of Sample Complexity for Multi-Item Profit Maximization
  with Maria-Florina Balcan and Tuomas Sandholm
  ACM Conference on Economics and Computation (EC) 2018
  [paper] [slides] [video]

• Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions
  with Bernhard Haeupler and Amirbehshad Shahrasbi
  International Colloquium on Automata, Languages and Programming (ICALP) 2018
  [paper]

• Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
  with Maria-Florina Balcan, Vaishnavh Nagarajan, and Colin White
  Conference on Learning Theory (COLT) 2017
  [paper] [slides]

• Sample Complexity of Automated Mechanism Design
  with Maria-Florina Balcan and Tuomas Sandholm
  Conference on Neural Information Processing Systems (NeurIPS) 2016
  [paper] [slides] [video]

• Learning Combinatorial Functions from Pairwise Comparisons
  with Maria-Florina Balcan and Colin White
  Conference on Learning Theory (COLT) 2016
  [paper]