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Brian Hu Zhang
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2020 – today
- 2024
- [c19]Brian Hu Zhang, Tuomas Sandholm:
On the Outcome Equivalence of Extensive-Form and Behavioral Correlated Equilibria. AAAI 2024: 9969-9976 - [c18]Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm:
Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games. ICLR 2024 - [c17]Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Manolis Zampetakis, Tuomas Sandholm, Paul Goldberg, Vincent Conitzer:
Imperfect-Recall Games: Equilibrium Concepts and Their Complexity. IJCAI 2024: 2994-3004 - [c16]Brian Hu Zhang, Tuomas Sandholm:
Exponential Lower Bounds on the Double Oracle Algorithm in Zero-Sum Games. IJCAI 2024: 3032-3039 - [c15]Brian Hu Zhang
, Gabriele Farina
Steering No-Regret Learners to a Desired Equilibrium. EC 2024: 73-74 - [c14]Luca Carminati
Hidden-Role Games: Equilibrium Concepts and Computation. EC 2024: 106-107 - [i20]Brian Hu Zhang, Tuomas Sandholm:
On the Outcome Equivalence of Extensive-Form and Behavioral Correlated Equilibria. CoRR abs/2402.05245 (2024) - [i19]Brian Hu Zhang, Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm:
Efficient Φ-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games. CoRR abs/2402.09670 (2024) - [i18]Brian Hu Zhang, Tuomas Sandholm:
Exponential Lower Bounds on the Double Oracle Algorithm in Zero-Sum Games. CoRR abs/2405.06797 (2024) - [i17]Constantinos Daskalakis, Gabriele Farina, Noah Golowich, Tuomas Sandholm, Brian Hu Zhang:
A Lower Bound on Swap Regret in Extensive-Form Games. CoRR abs/2406.13116 (2024) - [i16]Emanuel Tewolde, Brian Hu Zhang, Caspar Oesterheld, Manolis Zampetakis, Tuomas Sandholm, Paul W. Goldberg, Vincent Conitzer:
Imperfect-Recall Games: Equilibrium Concepts and Their Complexity. CoRR abs/2406.15970 (2024) - 2023
- [c13]Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm:
Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization. ICML 2023: 40996-41018 - [c12]Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides, Federico Cacciamani, Stephen McAleer, Andreas A. Haupt, Andrea Celli, Nicola Gatti, Vincent Conitzer, Tuomas Sandholm:
Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games. NeurIPS 2023 - [i15]Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides, Federico Cacciamani, Stephen Marcus McAleer, Andreas Alexander Haupt, Andrea Celli, Nicola Gatti, Vincent Conitzer, Tuomas Sandholm:
Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games. CoRR abs/2306.05216 (2023) - [i14]Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides, Federico Cacciamani, Stephen Marcus McAleer, Andreas Alexander Haupt, Andrea Celli, Nicola Gatti, Vincent Conitzer, Tuomas Sandholm:
Steering No-Regret Learners to Optimal Equilibria. CoRR abs/2306.05221 (2023) - [i13]Luca Carminati, Brian Hu Zhang, Gabriele Farina, Nicola Gatti, Tuomas Sandholm:
Hidden-Role Games: Equilibrium Concepts and Computation. CoRR abs/2308.16017 (2023) - [i12]Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm:
Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Extensive-Form Games. CoRR abs/2310.15935 (2023) - 2022
- [c11]Brian Hu Zhang, Tuomas Sandholm:
Team Correlated Equilibria in Zero-Sum Extensive-Form Games via Tree Decompositions. AAAI 2022: 5252-5259 - [c10]Pravesh K. Kothari, Peter Manohar, Brian Hu Zhang:
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally. ALT 2022: 638-667 - [c9]Brian Hu Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri, Nicola Gatti, Tuomas Sandholm:
Subgame Solving in Adversarial Team Games. NeurIPS 2022 - [c8]Brian Hu Zhang, Tuomas Sandholm:
Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games. NeurIPS 2022 - [c7]Brian Hu Zhang, Gabriele Farina, Andrea Celli, Tuomas Sandholm:
Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation. EC 2022: 1119-1120 - [i11]Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm:
Team Belief DAG Form: A Concise Representation for Team-Correlated Game-Theoretic Decision Making. CoRR abs/2202.00789 (2022) - [i10]Brian Hu Zhang, Gabriele Farina, Andrea Celli, Tuomas Sandholm:
Optimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation. CoRR abs/2203.07181 (2022) - [i9]Brian Hu Zhang, Tuomas Sandholm:
Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games. CoRR abs/2206.15395 (2022) - 2021
- [c6]Brian Hu Zhang, Tuomas Sandholm:
Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games. AAAI 2021: 5779-5788 - [c5]Brian Hu Zhang, Tuomas Sandholm:
Subgame solving without common knowledge. NeurIPS 2021: 23993-24004 - [i8]Brian Hu Zhang, Tuomas Sandholm:
Subgame solving without common knowledge. CoRR abs/2106.06068 (2021) - [i7]Brian Hu Zhang, Tuomas Sandholm:
Team Correlated Equilibria in Zero-Sum Extensive-Form Games via Tree Decompositions. CoRR abs/2109.05284 (2021) - [i6]Pravesh K. Kothari, Peter Manohar, Brian Hu Zhang:
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally. CoRR abs/2110.11853 (2021) - 2020
- [c4]Brian Hu Zhang, Tuomas Sandholm:
Sparsified Linear Programming for Zero-Sum Equilibrium Finding. ICML 2020: 11256-11267 - [c3]Brian Hu Zhang, Tuomas Sandholm:
Small Nash Equilibrium Certificates in Very Large Games. NeurIPS 2020 - [i5]Brian Hu Zhang, Tuomas Sandholm:
Sparsified Linear Programming for Zero-Sum Equilibrium Finding. CoRR abs/2006.03451 (2020) - [i4]Brian Hu Zhang, Tuomas Sandholm:
Small Nash Equilibrium Certificates in Very Large Games. CoRR abs/2006.16387 (2020) - [i3]Brian Hu Zhang, Tuomas Sandholm:
Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games. CoRR abs/2009.07384 (2020)
2010 – 2019
- 2018
- [c2]Brian Hu Zhang, Blake Lemoine, Margaret Mitchell:
Mitigating Unwanted Biases with Adversarial Learning. AIES 2018: 335-340 - [c1]Shivam Garg, Vatsal Sharan, Brian Hu Zhang, Gregory Valiant:
A Spectral View of Adversarially Robust Features. NeurIPS 2018: 10159-10169 - [i2]Brian Hu Zhang, Blake Lemoine, Margaret Mitchell:
Mitigating Unwanted Biases with Adversarial Learning. CoRR abs/1801.07593 (2018) - [i1]Shivam Garg, Vatsal Sharan, Brian Hu Zhang, Gregory Valiant:
A Spectral View of Adversarially Robust Features. CoRR abs/1811.06609 (2018)
Coauthor Index
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last updated on 2024-12-23 20:35 CET by the dblp team
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