5 citations · 13 across the 8 of their papers we have counts for
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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…
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 $…
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…