323 citations · 2.1k across the 72 of their papers we have counts for
6 papers · 1 filter
A Convex Formulation for Spectral Shrunk Clustering
Xiaojun Chang, Feiping Nie, Zhigang Ma +2
Spectral clustering is a fundamental technique in the field of data mining and information processing. Most existing spectral clustering algorithms integrate dimensionality reducti…
Balanced k-Means and Min-Cut Clustering
Xiaojun Chang, Feiping Nie, Zhigang Ma +1
Clustering is an effective technique in data mining to generate groups that are the matter of interest. Among various clustering approaches, the family of k-means algorithms and mi…
A Convex Sparse PCA for Feature Analysis
Xiaojun Chang, Feiping Nie, Yi Yang +1
Principal component analysis (PCA) has been widely applied to dimensionality reduction and data pre-processing for different applications in engineering, biology and social science…
Improved Spectral Clustering via Embedded Label Propagation
Xiaojun Chang, Feiping Nie, Yi Yang +1
Spectral clustering is a key research topic in the field of machine learning and data mining. Most of the existing spectral clustering algorithms are built upon Gaussian Laplacian…
Semi-supervised Feature Analysis by Mining Correlations among Multiple Tasks
Xiaojun Chang, Yi Yang
In this paper, we propose a novel semi-supervised feature selection framework by mining correlations among multiple tasks and apply it to different multimedia applications. Instead…
Compound Rank-k Projections for Bilinear Analysis
Xiaojun Chang, Feiping Nie, Sen Wang +3
In many real-world applications, data are represented by matrices or high-order tensors. Despite the promising performance, the existing two-dimensional discriminant analysis algor…