1.3k citations · 1.9k across the 46 of their papers we have counts for
4 papers · 1 filter
Balanced Coarsening for Multilevel Hypergraph Partitioning via Wasserstein Discrepancy
Zhicheng Guo, Jiaxuan Zhao, Licheng Jiao +1
We propose a balanced coarsening scheme for multilevel hypergraph partitioning. In addition, an initial partitioning algorithm is designed to improve the quality of k-way hypergrap…
Boosting Gradient for White-Box Adversarial Attacks
Hongying Liu, Zhenyu Zhou, Fanhua Shang +3
Deep neural networks (DNNs) are playing key roles in various artificial intelligence applications such as image classification and object recognition. However, a growing number of…
ASVRG: Accelerated Proximal SVRG
Fanhua Shang, Licheng Jiao, Kaiwen Zhou +3
This paper proposes an accelerated proximal stochastic variance reduced gradient (ASVRG) method, in which we design a simple and effective momentum acceleration trick. Unlike most…
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning
Fanhua Shang, Kaiwen Zhou, Hongying Liu +5
In this paper, we propose a simple variant of the original SVRG, called variance reduced stochastic gradient descent (VR-SGD). Unlike the choices of snapshot and starting points in…