Mitigating Unwanted Biases with Adversarial Learning. - Brian Hu Zhang; Blake Lemoine; Margaret Mitchell (AIES, 2018)

A Spectral View of Adversarially Robust Features. - Shivam Garg 001; Vatsal Sharan; Brian Hu Zhang; Gregory Valiant (NeurIPS, 2018)

Sparsified Linear Programming for Zero-Sum Equilibrium Finding. - Brian Hu Zhang; Tuomas Sandholm (ICML, 2020)

Small Nash Equilibrium Certificates in Very Large Games. - Brian Hu Zhang; Tuomas Sandholm (NeurIPS, 2020)

Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games. - Brian Hu Zhang; Tuomas Sandholm (AAAI, 2021)

Subgame solving without common knowledge. - Brian Hu Zhang; Tuomas Sandholm (NeurIPS, 2021)

Team Correlated Equilibria in Zero-Sum Extensive-Form Games via Tree Decompositions. - Brian Hu Zhang; Tuomas Sandholm (AAAI, 2022)

Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally. - Pravesh K. Kothari; Peter Manohar; Brian Hu Zhang (ALT, 2022)

Subgame Solving in Adversarial Team Games. - Brian Hu Zhang; Luca Carminati; Federico Cacciamani; Gabriele Farina; Pierriccardo Olivieri; Nicola Gatti 001; Tuomas Sandholm (NeurIPS, 2022)

Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games. - Brian Hu Zhang; Tuomas Sandholm (NeurIPS, 2022)

Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation. - Brian Hu Zhang; Gabriele Farina; Andrea Celli; Tuomas Sandholm (EC, 2022)

Team Belief DAG Form: A Concise Representation for Team-Correlated Game-Theoretic Decision Making. - Brian Hu Zhang; Gabriele Farina; Tuomas Sandholm (CoRR, 2022)

Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization. - Brian Hu Zhang; Gabriele Farina; Tuomas Sandholm (ICML, 2023)

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen McAleer; Andreas A. Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (NeurIPS, 2023)

Steering No-Regret Learners to Optimal Equilibria. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen Marcus McAleer; Andreas Alexander Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (CoRR, 2023)

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Extensive-Form Games. - Brian Hu Zhang; Gabriele Farina; Tuomas Sandholm (CoRR, 2023)

On the Outcome Equivalence of Extensive-Form and Behavioral Correlated Equilibria. - Brian Hu Zhang; Tuomas Sandholm (AAAI, 2024)

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games. - Brian Hu Zhang; Gabriele Farina; Tuomas Sandholm (ICLR, 2024)

Imperfect-Recall Games: Equilibrium Concepts and Their Complexity. - Emanuel Tewolde; Brian Hu Zhang; Caspar Oesterheld; Manolis Zampetakis; Tuomas Sandholm; Paul Goldberg 001; Vincent Conitzer (IJCAI, 2024)

Exponential Lower Bounds on the Double Oracle Algorithm in Zero-Sum Games. - Brian Hu Zhang; Tuomas Sandholm (IJCAI, 2024)

Efficient $ Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. - Brian Hu Zhang; Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm (NeurIPS, 2024)

Hidden-Role Games: Equilibrium Concepts and Computation. - Luca Carminati; Brian Hu Zhang; Gabriele Farina; Nicola Gatti 001; Tuomas Sandholm (EC, 2024)

Steering No-Regret Learners to a Desired Equilibrium. - Brian Hu Zhang; Gabriele Farina; Ioannis Anagnostides; Federico Cacciamani; Stephen McAleer; Andreas A. Haupt; Andrea Celli; Nicola Gatti 001; Vincent Conitzer; Tuomas Sandholm (EC, 2024)

Efficient Φ-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. - Brian Hu Zhang; Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm (CoRR, 2024)

A Lower Bound on Swap Regret in Extensive-Form Games. - Constantinos Daskalakis; Gabriele Farina; Noah Golowich; Tuomas Sandholm; Brian Hu Zhang (CoRR, 2024)

Computing Game Symmetries and Equilibria That Respect Them. - Emanuel Tewolde; Brian Hu Zhang; Caspar Oesterheld; Tuomas Sandholm; Vincent Conitzer (AAAI, 2025)

Learning and Computation of Φ-Equilibria at the Frontier of Tractability. - Brian Hu Zhang; Ioannis Anagnostides; Emanuel Tewolde; Ratip Emin Berker; Gabriele Farina; Vincent Conitzer; Tuomas Sandholm (EC, 2025)

Expected Variational Inequalities. - Brian Hu Zhang; Ioannis Anagnostides; Emanuel Tewolde; Ratip Emin Berker; Gabriele Farina; Vincent Conitzer; Tuomas Sandholm (CoRR, 2025)

Learning a Game by Paying the Agents. - Brian Hu Zhang; Tao Lin; Yiling Chen; Tuomas Sandholm (CoRR, 2025)

A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition. - Ioannis Anagnostides; Gabriele Farina; Tuomas Sandholm; Brian Hu Zhang (CoRR, 2025)

General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess. - Brian Hu Zhang; Tuomas Sandholm (CoRR, 2025)