243 citations · 392 across the 23 of their papers we have counts for
5 papers · 1 filter
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack
Haishan Ye, Zhichao Huang, Cong Fang +2
Zeroth-order optimization is an important research topic in machine learning. In recent years, it has become a key tool in black-box adversarial attack to neural network based imag…
Lifted Proximal Operator Machines
Jia Li, Cong Fang, Zhouchen Lin
We propose a new optimization method for training feed-forward neural networks. By rewriting the activation function as an equivalent proximal operator, we approximate a feed-forwa…
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…
Accelerating Asynchronous Algorithms for Convex Optimization by Momentum Compensation
Cong Fang, Yameng Huang, Zhouchen Lin
Asynchronous algorithms have attracted much attention recently due to the crucial demands on solving large-scale optimization problems. However, the accelerated versions of asynchr…