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AAAI
2015

A Convex Formulation for Spectral Shrunk Clustering

4 years 4 days ago
A Convex Formulation for Spectral Shrunk Clustering
Spectral clustering is a fundamental technique in the field of data mining and information processing. Most existing spectral clustering algorithms integrate dimensionality reduction into the clustering process assisted by manifold learning in the original space. However, the manifold in reduced-dimensional subspace is likely to exhibit altered properties in contrast with the original space. Thus, applying manifold information obtained from the original space to the clustering process in a low-dimensional subspace is prone to inferior performance. Aiming to address this issue, we propose a novel convex algorithm that mines the manifold structure in the low-dimensional subspace. In addition, our unified learning process makes the manifold learning particularly tailored for the clustering. Compared with other related methods, the proposed algorithm results in more structured clustering result. To validate the efficacy of the proposed algorithm, we perform extensive experiments on sev...
Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang, X
Added 27 Mar 2016
Updated 27 Mar 2016
Type Journal
Year 2015
Where AAAI
Authors Xiaojun Chang, Feiping Nie, Zhigang Ma, Yi Yang, Xiaofang Zhou
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