26 citations · 77 across the 12 of their papers we have counts for
7 papers · 1 filter
Matching Higher-Order Oracle Complexity for Smooth Monotone Variational Inequalities
Haihan Zhang, Wendao Wu, Chenheng Zhang +3
We establish near-optimal higher-order oracle bounds for smooth monotone variational inequalities. For fixed , let be monotone on a known compact convex set of diame…
Zeroth-order Optimization with Weak Dimension Dependency
Pengyun Yue, Long Yang, Cong Fang +1
Zeroth-order optimization is a fundamental research topic that has been a focus of various learning tasks, such as black-box adversarial attacks, bandits, and reinforcement learnin…
A Stochastic Trust Region Method for Non-convex Minimization
Zebang Shen, Pan Zhou, Cong Fang +1
We target the problem of finding a local minimum in non-convex finite-sum minimization. Towards this goal, we first prove that the trust region method with inexact gradient and Hes…
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points
Cong Fang, Zhouchen Lin, Tong Zhang
In this paper, we give a sharp analysis for Stochastic Gradient Descent (SGD) and prove that SGD is able to efficiently escape from saddle points and find an -appr…
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters
Huan Li, Cong Fang, Wotao Yin +1
In this paper, we study the communication and (sub)gradient computation costs in distributed optimization and give a sharp complexity analysis for the proposed distributed accelera…
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator
Cong Fang, Chris Junchi Li, Zhouchen Lin +1
In this paper, we propose a new technique named \textit{Stochastic Path-Integrated Differential EstimatoR} (SPIDER), which can be used to track many deterministic quantities of int…