18 citations · 59 across the 19 of their papers we have counts for
6 papers · 1 filter
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 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…
Deterministic Nonsmooth Nonconvex Optimization
Michael I. Jordan, Guy Kornowski, Tianyi Lin +2
We study the complexity of optimizing nonsmooth nonconvex Lipschitz functions by producing -stationary points. Several recent works have presented randomized algorithms that…
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback
Tianyi Lin, Aldo Pacchiano, Yaodong Yu +1
Motivated by applications to online learning in sparse estimation and Bayesian optimization, we consider the problem of online unconstrained nonsubmodular minimization with delayed…
Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback
Wenjia Ba, Tianyi Lin, Jiawei Zhang +1
We consider online no-regret learning in unknown games with bandit feedback, where each player can only observe its reward at each time -- determined by all players' current joint…
Projection Robust Wasserstein Distance and Riemannian Optimization
Tianyi Lin, Chenyou Fan, Nhat Ho +2
Projection robust Wasserstein (PRW) distance, or Wasserstein projection pursuit (WPP), is a robust variant of the Wasserstein distance. Recent work suggests that this quantity is m…