1 citations · 1 across the 5 of their papers we have counts for
5 papers
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Tianyi Lin, Chi Jin, Michael. I. Jordan
We provide a unified analysis of two-timescale gradient descent ascent (TTGDA) for solving structured nonconvex minimax optimization problems in the form of $\min_\textbf{x} \max_{…
A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games
Francisca Vasconcelos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos +2
Recent developments in domains such as non-local games, quantum interactive proofs, and quantum generative adversarial networks have renewed interest in quantum game theory and, sp…
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
Tianyi Lin, Marco Cuturi, Michael I. Jordan
Kernel-based optimal transport (OT) estimators offer an alternative, functional estimation procedure to address OT problems from samples. Recent works suggest that these estimators…
Adaptive, Doubly Optimal No-Regret Learning in Strongly Monotone and Exp-Concave Games with Gradient Feedback
Michael I. Jordan, Tianyi Lin, Zhengyuan Zhou
Online gradient descent (OGD) is well known to be doubly optimal under strong convexity or monotonicity assumptions: (1) in the single-agent setting, it achieves an optimal regret…
Explicit Second-Order Min-Max Optimization: Practical Algorithms and Complexity Analysis
Tianyi Lin, Panayotis Mertikopoulos, Michael I. Jordan
We propose and analyze several inexact regularized Newton-type methods for finding a global saddle point of convex-concave unconstrained min-max optimization problems. Compared to…