activity
20112023
most citedA relative error estimation approach for single index model

4 citations · 5 across the 10 of their papers we have counts for

collaborators

12 papers

stat.ML2023

Distributed sequential federated learning

Z. F. Wang, X. Y. Zhang, Y-c I. Chang

The analysis of data stored in multiple sites has become more popular, raising new concerns about the security of data storage and communication. Federated learning, which does not…

stat.ME2019

Sequential estimation for GEE with adaptive variables and subject selection

Zimu Chen, Zhanfeng Wang, Yuan-chin Ivan Chang

Modeling correlated or highly stratified multiple-response data becomes a common data analysis task due to modern data monitoring facilities and methods. Generalized estimating equ…

stat.ME2019

Modeling Function-Valued Processes with Nonseparable and/or Nonstationary Covariance Structure

Evandro Konzen, Jian Qing Shi, Zhanfeng Wang

We discuss a general Bayesian framework on modeling multidimensional function-valued processes by using a Gaussian process or a heavy-tailed process as a prior, enabling us to hand…

stat.ML2019★ 1 cited

Active learning for binary classification with variable selection

Zhanfeng Wang, Yumi Kwon, Yuan-chin Ivan Chang

Modern computing and communication technologies can make data collection procedures very efficient. However, our ability to analyze large data sets and/or to extract information ou…

stat.ME2018

Distributed sequential method for analyzing massive data

Zhanfeng Wang, Yuan-chin Ivan Chang

To analyse a very large data set containing lengthy variables, we adopt a sequential estimation idea and propose a parallel divide-and-conquer method. We conduct several convention…

stat.AP2018

A robust estimation for the extended t-process regression model

Zhanfeng Wang, Kai Li, Jian Qing Shi

Robust estimation and variable selection procedure are developed for the extended t-process regression model with functional data. Statistical properties such as consistency of est…