5 citations · 13 across the 8 of their papers we have counts for
8 papers
An Accelerated Block Proximal Framework with Adaptive Momentum for Nonconvex and Nonsmooth Optimization
Weifeng Yang, Wenwen Min
We propose an accelerated block proximal linear framework with adaptive momentum (ABPL) for nonconvex and nonsmooth optimization. We analyze the potential causes of the extrapo…
Weighted Sparse Partial Least Squares for Joint Sample and Feature Selection
Wenwen Min, Taosheng Xu, Chris Ding
Sparse Partial Least Squares (sPLS) is a common dimensionality reduction technique for data fusion, which projects data samples from two views by seeking linear combinations with a…
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data Analysis
Wenwen Min, Taosheng Xu, Xiang Wan +1
Non-negative matrix factorization (NMF) is a powerful tool for dimensionality reduction and clustering. Unfortunately, the interpretation of the clustering results from NMF is diff…
Group-sparse SVD Models and Their Applications in Biological Data
Wenwen Min, Juan Liu, Shihua Zhang
Sparse Singular Value Decomposition (SVD) models have been proposed for biclustering high dimensional gene expression data to identify block patterns with similar expressions. Howe…
Sparse Weighted Canonical Correlation Analysis
Wenwen Min, Juan Liu, Shihua Zhang
Given two data matrices and , sparse canonical correlation analysis (SCCA) is to seek two sparse canonical vectors and to maximize the correlation between and $…
Network-regularized Sparse Logistic Regression Models for Clinical Risk Prediction and Biomarker Discovery
Wenwen Min, Juan Liu, Shihua Zhang
Molecular profiling data (e.g., gene expression) has been used for clinical risk prediction and biomarker discovery. However, it is necessary to integrate other prior knowledge lik…
L0-norm Sparse Graph-regularized SVD for Biclustering
Wenwen Min, Juan Liu, Shihua Zhang
Learning the "blocking" structure is a central challenge for high dimensional data (e.g., gene expression data). Recently, a sparse singular value decomposition (SVD) has been used…
A neurodynamic framework for local community extraction in networks
Shihua Zhang, Guanghua Hu, Wenwen Min
To understand the structure and organization of a large-scale social, biological or technological network, it can be helpful to describe and extract local communities or modules of…