Cyrus Cousins

CoRR, 2024

On Welfare-Centric Fair Reinforcement Learning.

[BibT_eX]

RLJ, 2024

To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models.

[BibT_eX]

[DOI]

Suresh Venkatasubramanian

I. Elizabeth Kumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Bavarian: Betweenness Centrality Approximation with Variance-aware Rademacher Averages.

[BibT_eX]

[DOI]

Chloe Wohlgemuth

Matteo Riondato

ACM Trans. Knowl. Discov. Data, July, 2023

Dividing Good and Better Items Among Agents with Submodular Valuations.

[BibT_eX]

[DOI]

Vignesh Viswanathan

CoRR, 2023

Dividing Good and Great Items Among Agents with Bivalued Submodular Valuations.

[BibT_eX]

[DOI]

Vignesh Viswanathan

Proceedings of the Web and Internet Economics - 19th International Conference, 2023

The Good, the Bad and the Submodular: Fairly Allocating Mixed Manna Under Order-Neutral Submodular Preferences.

[BibT_eX]

[DOI]

Vignesh Viswanathan

Proceedings of the Web and Internet Economics - 19th International Conference, 2023

Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities.

[BibT_eX]

[DOI]

Justin Payan

Proceedings of the Algorithmic Game Theory - 16th International Symposium, 2023

Percentile Criterion Optimization in Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Properties in Simulation-Based Games.

[BibT_eX]

[DOI]

Bhaskar Mishra

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2022

Regret Pruning for Learning Equilibria in Simulation-Based Games.

[BibT_eX]

[DOI]

Bhaskar Mishra

CoRR, 2022

Computational and Data Requirements for Learning Generic Properties of Simulation-Based Games.

[BibT_eX]

[DOI]

Bhaskar Mishra

CoRR, 2022

Uncertainty and the Social Planner's Problem: Why Sample Complexity Matters.

[BibT_eX]

[DOI]

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Bounds and Applications of Concentration of Measure in Fair Machine Learning and Data Science.

[BibT_eX]

[DOI]

PhD thesis, 2021

Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Competitive Equilibria in Noisy Combinatorial Markets.

[BibT_eX]

[DOI]

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE.

[BibT_eX]

[DOI]

Shahrzad Haddadan

CoRR, 2020

Sharp uniform convergence bounds through empirical centralization.

[BibT_eX]

[DOI]

Matteo Riondato

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improved Algorithms for Learning Equilibria in Simulation-Based Games.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

CaDET: interpretable parametric conditional density estimation with decision trees and forests.

[BibT_eX]

[DOI]

Matteo Riondato

Mach. Learn., 2019

Learning Equilibria of Simulation-Based Games.

[BibT_eX]

[DOI]

CoRR, 2019

Empirical Mechanism Design: Designing Mechanisms from Data.

[BibT_eX]

[DOI]

Yasser Mohammad

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Learning Simulation-Based Games from Data.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Uniform Convergence Bounds for Codec Selection.

[BibT_eX]

[DOI]

Clayton Sanford

CoRR, 2018

Towards Interactive Curation & Automatic Tuning of ML Pipelines.

[BibT_eX]

[DOI]

Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, 2018

2017

Scalable FRaC Variants: Anomaly Detection for Precision Medicine.

[BibT_eX]

[DOI]

Christopher M. Pietras

Donna K. Slonim

Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium Workshops, 2017

The k-Nearest Representatives Classifier: A Distance-Based Classifier with Strong Generalization Bounds.

[BibT_eX]

[DOI]