Robust subspace learning-based low-rank representation for manifold clustering
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DOI: 10.1007/s00521-018-3617-8
Abstract: Spectral clustering-based subspace clustering methods have attracted broad interest in recent years. This kind of methods usually uses the self-representation in the original space to extract the affinity between the data points. However, we can… read more here.
Keywords: rank representation; manifold clustering; subspace; low rank ... See more keywords
A Nonparametric Model for Multi-Manifold Clustering with Mixture of Gaussians and Graph Consistency
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DOI: 10.3390/e20110830
Abstract: Multi-manifold clustering is among the most fundamental tasks in signal processing and machine learning. Although the existing multi-manifold clustering methods are quite powerful, learning the cluster number automatically from data is still a challenge. In… read more here.
Keywords: manifold clustering; model; mixture gaussians; multi manifold ... See more keywords