18 citations · 59 across the 19 of their papers we have counts for
4 papers · 1 filter
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…
Last-Iterate Convergence of Adaptive Riemannian Gradient Descent for Equilibrium Computation
Yang Cai, Michael I. Jordan, Tianyi Lin +2
Equilibrium computation on Riemannian manifolds provides a unifying framework for numerous problems in machine learning and data analytics. One of the simplest yet most fundamental…
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…