Improving K-Subspaces via Coherence Pursuit.
IEEE Journal of Selected Topics in Signal Processing(2018)
摘要
Subspace clustering is a powerful generalization of clustering for high-dimensional data analysis, where low-rank cluster structure is leveraged for accurate inference. K-Subspaces (KSS), an alternating algorithm that mirrors K-means, is a classical approach for clustering with this model. Like K-means, KSS is highly sensitive to initialization, yet KSS has two major handicaps beyond this issue. F...
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关键词
Clustering algorithms,Signal processing algorithms,Principal component analysis,Robustness,Algorithm design and analysis
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