212 citations · 419 across the 46 of their papers we have counts for
8 papers · 1 filter
Accelerating Inexact HyperGradient Descent for Bilevel Optimization
Haikuo Yang, Luo Luo, Chris Junchi Li +1
We present a method for solving general nonconvex-strongly-convex bilevel optimization problems. Our method -- the \emph{Restarted Accelerated HyperGradient Descent} (\texttt{RAHGD…
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…
Accelerated First-Order Optimization under Nonlinear Constraints
Michael Muehlebach, Michael I. Jordan
We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of accelerated first-order algorithms for co…
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization
Tianyi Lin, Zeyu Zheng, Michael I. Jordan
Nonsmooth nonconvex optimization problems broadly emerge in machine learning and business decision making, whereas two core challenges impede the development of efficient solution…
Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization
Chris Junchi Li, Angela Yuan, Gauthier Gidel +2
We propose a new first-order optimization algorithm -- AcceleratedGradient-OptimisticGradient (AG-OG) Descent Ascent -- for separable convex-concave minimax optimization. The main…
On the Complexity of Deterministic Nonsmooth and Nonconvex Optimization
Michael I. Jordan, Tianyi Lin, Manolis Zampetakis
In this paper, we present several new results on minimizing a nonsmooth and nonconvex function under a Lipschitz condition. Recent work shows that while the classical notion of Cla…
Perseus: A Simple and Optimal High-Order Method for Variational Inequalities
Tianyi Lin, Michael. I. Jordan
This paper settles an open and challenging question pertaining to the design of simple and optimal high-order methods for solving smooth and monotone variational inequalities (VIs)…
On the Stability of Nonlinear Receding Horizon Control: A Geometric Perspective
Tyler Westenbroek, Max Simchowitz, Michael I. Jordan +1
%!TEX root = LCSS_main_max.tex The widespread adoption of nonlinear Receding Horizon Control (RHC) strategies by industry has led to more than 30 years of intense research efforts…