No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian
Processes

No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes

Conference on Uncertainty in Artificial Intelligence (UAI), 2024

14 May 2024

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Papers citing "No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes"

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Title
Multi-Fidelity Bayesian Optimization for Nash Equilibria with Black-Box Utilities Yunchuan Zhang Osvaldo Simeone H. Vincent Poor 257 1 0 16 May 2025
A Framework for Finding Local Saddle Points in Two-Player Zero-Sum Black-Box Games Shubhankar Agarwal Hamzah I. Khan Sandeep Chinchali David Fridovich-Keil 279 1 0 23 Mar 2025
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein DesignInternational Conference on Learning Representations (ICLR), 2024 Melis Ilayda Bal Pier Giuseppe Sessa Mojmír Mutný Andreas Krause 357 2 0 27 Sep 2024
Transition Constrained Bayesian Optimization via Markov Decision Processes Jose Pablo Folch Calvin Tsay Robert M. Lee B. Shafei Weronika Ormaniec Andreas Krause Mark van der Wilk Ruth Misener Mojmír Mutný 355 7 0 13 Feb 2024