activity
20152019
most citedEfficient Projection-Free Online Methods with Stochastic Recursive Gradient

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2022

SIGMA: A Structural Inconsistency Reducing Graph Matching Algorithm

Weijie Liu, Chao Zhang, Nenggan Zheng +1

Graph matching finds the correspondence of nodes across two correlated graphs and lies at the core of many applications. When graph side information is not available, the node corr…

cs.LG20192 cited

Efficient Projection-Free Online Methods with Stochastic Recursive Gradient

Jiahao Xie, Zebang Shen, Chao Zhang +2

This paper focuses on projection-free methods for solving smooth Online Convex Optimization (OCO) problems. Existing projection-free methods either achieve suboptimal regret bounds…

cs.LG2019

Aggregated Gradient Langevin Dynamics

Chao Zhang, Jiahao Xie, Zebang Shen +3

In this paper, we explore a general Aggregated Gradient Langevin Dynamics framework (AGLD) for the Markov Chain Monte Carlo (MCMC) sampling. We investigate the nonasymptotic conver…

stat.ML2018

Towards More Efficient Stochastic Decentralized Learning: Faster Convergence and Sparse Communication

Zebang Shen, Aryan Mokhtari, Tengfei Zhou +2

Recently, the decentralized optimization problem is attracting growing attention. Most existing methods are deterministic with high per-iteration cost and have a convergence rate q…

cs.IT2015

A Nonconvex Approach for Structured Sparse Learning

Shubao Zhang, Hui Qian, Zhihua Zhang

Sparse learning is an important topic in many areas such as machine learning, statistical estimation, signal processing, etc. Recently, there emerges a growing interest on structur…