16 citations · 190 across the 78 of their papers we have counts for
5 papers · 1 filter
A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
David Yang, Yuan Gao, Tianyi Lin +1
We introduce, to our knowledge, the first direct second-order method for computing Nash equilibria in two-player zero-sum games. To do so, we construct a Douglas-Rachford-style spl…
The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub +3
Data-driven stochastic optimization is ubiquitous in machine learning and operational decision-making problems. Sample average approximation (SAA) and model-based approaches such a…
Strongly Convex Maximization via the Frank-Wolfe Algorithm with the Kurdyka-Łojasiewicz Inequality
Fatih Selim Aktas, Christian Kroer
We study the convergence properties of the 'greedy' Frank-Wolfe algorithm with a unit step size, for a convex maximization problem over a compact set. We assume the function satisf…
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…
Computing Lindahl Equilibrium for Public Goods with and without Funding Caps
Christian Kroer, Dominik Peters
Lindahl equilibrium is a solution concept for allocating a fixed budget across several divisible public goods. It always lies in the weak core, meaning that the equilibrium allocat…