activity
20182022
most citedEfficient Estimation for Generalized Linear Models on a Distributed System with Nonrandomly Distributed Data

1 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2022

Network Gradient Descent Algorithm for Decentralized Federated Learning

Shuyuan Wu, Danyang Huang, Hansheng Wang

We study a fully decentralized federated learning algorithm, which is a novel gradient descent algorithm executed on a communication-based network. For convenience, we refer to it…

stat.ME20211 cited

A Sequential Addressing Subsampling Method for Massive Data Analysis under Memory Constraint

Rui Pan, Yingqiu Zhu, Baishan Guo +2

The emergence of massive data in recent years brings challenges to automatic statistical inference. This is particularly true if the data are too numerous to be read into memory as…

stat.ME20211 cited

On the Subbagging Estimation for Massive Data

Tao Zou, Xian Li, Xuan Liang +1

This article introduces subbagging (subsample aggregating) estimation approaches for big data analysis with memory constraints of computers. Specifically, for the whole dataset wit…

stat.ME20201 cited

Efficient Estimation for Generalized Linear Models on a Distributed System with Nonrandomly Distributed Data

Feifei Wang, Danyang Huang, Yingqiu Zhu +1

Distributed systems have been widely used in practice to accomplish data analysis tasks of huge scales. In this work, we target on the estimation problem of generalized linear mode…

stat.ME2018

Banded Spatio-Temporal Autoregressions

Zhaoxing Gao, Yingying Ma, Hansheng Wang +1

We propose a new class of spatio-temporal models with unknown and banded autoregressive coefficient matrices. The setting represents a sparse structure for high-dimensional spatial…