most citedSpectral Sparse Representation for Clustering: Evolved from PCA, K-means, Laplacian Eigenmap, and Ratio Cut

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

collaborators

3 papers

cs.LG2017

Spectral-graph Based Classifications: Linear Regression for Classification and Normalized Radial Basis Function Network

Zhenfang Hu, Gang Pan, Zhaohui Wu

Spectral graph theory has been widely applied in unsupervised and semi-supervised learning. In this paper, we find for the first time, to our knowledge, that it also plays a concre…

cs.LG2014★ 2 cited

Sparse Principal Component Analysis via Rotation and Truncation

Zhenfang Hu, Gang Pan, Yueming Wang +1

Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, meanwhile the sparse basis should cover…

cs.CV2014★ 2 cited

Spectral Sparse Representation for Clustering: Evolved from PCA, K-means, Laplacian Eigenmap, and Ratio Cut

Zhenfang Hu, Gang Pan, Yueming Wang +1

Dimensionality reduction, cluster analysis, and sparse representation are basic components in machine learning. However, their relationships have not yet been fully investigated. I…