11 citations · 31 across the 6 of their papers we have counts for
6 papers
A Model Parallel Proximal Stochastic Gradient Algorithm for Partially Asynchronous Systems
Rui Zhu, Di Niu
Large models are prevalent in modern machine learning scenarios, including deep learning, recommender systems, etc., which can have millions or even billions of parameters. Paralle…
Android Malware Detection using Large-scale Network Representation Learning
Rui Zhu, Chenglin Li, Di Niu +2
With the growth of mobile devices and applications, the number of malicious software, or malware, is rapidly increasing in recent years, which calls for the development of advanced…
Android Malware Detection based on Factorization Machine
Chenglin Li, Keith Mills, Rui Zhu +3
As the popularity of Android smart phones has increased in recent years, so too has the number of malicious applications. Due to the potential for data theft mobile phone users fac…
A Block-wise, Asynchronous and Distributed ADMM Algorithm for General Form Consensus Optimization
Rui Zhu, Di Niu, Zongpeng Li
Many machine learning models, including those with non-smooth regularizers, can be formulated as consensus optimization problems, which can be solved by the alternating direction m…
Asynchronous Stochastic Proximal Methods for Nonconvex Nonsmooth Optimization
Rui Zhu, Di Niu, Zongpeng Li
We study stochastic algorithms for solving nonconvex optimization problems with a convex yet possibly nonsmooth regularizer, which find wide applications in many practical machine…
Expectile Matrix Factorization for Skewed Data Analysis
Rui Zhu, Di Niu, Linglong Kong +1
Matrix factorization is a popular approach to solving matrix estimation problems based on partial observations. Existing matrix factorization is based on least squares and aims to…