Affinity learning via a diffusion process for subspace clustering

Affinity learning via a diffusion process for subspace clustering

Subspace clustering refers to the problem of finding low-dimensional subspaces (clusters) for high-dimensional data. Current state-of-the-art subspace clustering methods are usually based on spectral clustering, where an affinity matrix is learned by the self-expressive model, i.e., reconstructing e...

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Bibliographic Details
Main Authors: Li, Q., Liu, Wan-Quan, Li, Ling
Format: Journal Article
Published: Elsevier 2018
Online Access:http://hdl.handle.net/20.500.11937/69801

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