1 citations · 1 across the 1 of their papers we have counts for
5 papers
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…
Voluntary Renewable Programs: Optimal Pricing and Revenue Allocation
Zhiyuan Fan, Tianyi Lin, Bolun Xu
This paper develops a multi-period optimization framework to design a voluntary renewable program (VRP) for an electric utility company, aiming to maximize total renewable energy d…
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 th…
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_{…