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Evan Faulkner

2 accepted papers

2022

Learning in Stochastic Monotone Games with Decision-Dependent Data

AISTATS 2022poster

Learning problems commonly exhibit an interesting feedback mechanism wherein the population data reacts to competing decision makers’ actions. This paper formulates a new game theoretic framework for this phenomenon, called multi-player performative prediction. We establish transparent sufficient co…

Cited by 20SourcePDFScholar
2021

Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games

NeurIPS 2021poster

We study gradient descent-ascent learning dynamics with timescale separation ($\tau$-GDA) in unconstrained continuous action zero-sum games where the minimizing player faces a nonconvex optimization problem and the maximizing player optimizes a Polyak-Lojasiewicz (PL) or strongly-concave (SC) object…

Cited by 36SourcePDFScholar