Brian Hu Zhang

According to our database, Brian Hu Zhang authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

On the Outcome Equivalence of Extensive-Form and Behavioral Correlated Equilibria.

Brian Hu Zhang, Tuomas Sandholm

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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

Hidden-Role Games: Equilibrium Concepts and Computation.

Luca Carminati, Brian Hu Zhang, Gabriele Farina, Nicola Gatti, Tuomas Sandholm

CoRR, 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, Vincent Conitzer, Tuomas Sandholm

CoRR, 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, Vincent Conitzer, Tuomas Sandholm

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

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

Proceedings of the International Conference on Machine Learning, 2023

2022

Team Belief DAG Form: A Concise Representation for Team-Correlated Game-Theoretic Decision Making.

Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm

CoRR, 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

Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games.

Brian Hu Zhang, Tuomas Sandholm

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Subgame Solving in Adversarial Team Games.

Brian Hu Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri, Nicola Gatti, Tuomas Sandholm

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally.

Pravesh K. Kothari, Peter Manohar, Brian Hu Zhang

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Team Correlated Equilibria in Zero-Sum Extensive-Form Games via Tree Decompositions.

Brian Hu Zhang, Tuomas Sandholm

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Subgame solving without common knowledge.

Brian Hu Zhang, Tuomas Sandholm

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

Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games.

Brian Hu Zhang, Tuomas Sandholm

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Small Nash Equilibrium Certificates in Very Large Games.

Brian Hu Zhang, Tuomas Sandholm

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

Sparsified Linear Programming for Zero-Sum Equilibrium Finding.

Brian Hu Zhang, Tuomas Sandholm

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

A Spectral View of Adversarially Robust Features.

Shivam Garg, Vatsal Sharan, Brian Hu Zhang, Gregory Valiant

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Mitigating Unwanted Biases with Adversarial Learning.

Brian Hu Zhang, Blake Lemoine, Margaret Mitchell

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018