16 citations · 190 across the 78 of their papers we have counts for
9 papers · 1 filter
On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
Yang Cai, Gabriele Farina, Julien Grand-Clément +4
Non-ergodic convergence of learning dynamics in games is widely studied recently because of its importance in both theory and practice. Recent work (Cai et al., 2024) showed that a…
On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games
Zhiyuan Fan, Christian Kroer, Gabriele Farina
First-order methods (FOMs) are arguably the most scalable algorithms for equilibrium computation in large extensive-form games. To operationalize these methods, a distance-generati…
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games
Samuel Sokota, Ryan D'Orazio, J. Zico Kolter +5
This work studies an algorithm, which we call magnetic mirror descent, that is inspired by mirror descent and the non-Euclidean proximal gradient algorithm. Our contribution is dem…
Best of Many Worlds Guarantees for Online Learning with Knapsacks
Andrea Celli, Matteo Castiglioni, Christian Kroer
We study online learning problems in which a decision maker wants to maximize their expected reward without violating a finite set of resource constraints. By casting the learn…
Last-iterate Convergence in Extensive-Form Games
Chung-Wei Lee, Christian Kroer, Haipeng Luo
Regret-based algorithms are highly efficient at finding approximate Nash equilibria in sequential games such as poker games. However, most regret-based algorithms, including counte…
Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
Julien Grand-Clément, Christian Kroer
We develop new parameter-free and scale-free algorithms for solving convex-concave saddle-point problems. Our results are based on a new simple regret minimizer, the Conic Blackwel…
Evaluating and Rewarding Teamwork Using Cooperative Game Abstractions
Tom Yan, Christian Kroer, Alexander Peysakhovich
Can we predict how well a team of individuals will perform together? How should individuals be rewarded for their contributions to the team performance? Cooperative game theory giv…
Increasing Iterate Averaging for Solving Saddle-Point Problems
Yuan Gao, Christian Kroer, Donald Goldfarb
Many problems in machine learning and game theory can be formulated as saddle-point problems, for which various first-order methods have been developed and proven efficient in prac…
Regret Circuits: Composability of Regret Minimizers
Gabriele Farina, Christian Kroer, Tuomas Sandholm
Regret minimization is a powerful tool for solving large-scale problems; it was recently used in breakthrough results for large-scale extensive-form game solving. This was achieved…