activity
20192021
most citedDenoising individual bias for a fairer binary submatrix detection

4 citations · 4 across the 2 of their papers we have counts for

collaborators

5 papers

stat.ME2021

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

Wennan Chang, Pengtao Dang, Changlin Wan +7

In this paper, we propose a Spatial Robust Mixture Regression model to investigate the relationship between a response variable and a set of explanatory variables over the spatial…

cs.LG20204 cited

Denoising individual bias for a fairer binary submatrix detection

Changlin Wan, Wennan Chang, Tong Zhao +2

Low rank representation of binary matrix is powerful in disentangling sparse individual-attribute associations, and has received wide applications. Existing binary matrix factoriza…

cs.LG2020

Geometric All-Way Boolean Tensor Decomposition

Changlin Wan, Wennan Chang, Tong Zhao +2

Boolean tensor has been broadly utilized in representing high dimensional logical data collected on spatial, temporal and/or other relational domains. Boolean Tensor Decomposition…

stat.ME2020

Component-wise Adaptive Trimming For Robust Mixture Regression

Wennan Chang, Xinyu Zhou, Yong Zang +2

Parameter estimation of mixture regression model using the expectation maximization (EM) algorithm is highly sensitive to outliers. Here we propose a fast and efficient robust mixt…

cs.LG2019

Fast And Efficient Boolean Matrix Factorization By Geometric Segmentation

Changlin Wan, Wennan Chang, Tong Zhao +3

Boolean matrix has been used to represent digital information in many fields, including bank transaction, crime records, natural language processing, protein-protein interaction, e…