Improving Spectral Clustering Using Spectrum-Preserving Node Aggregation
Author:
Affiliation:
1. University of Southern California,Department of Electrical and Computer Engineering,Los Angeles,California,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9956007/9955631/09956605.pdf?arnumber=9956605
Reference34 articles.
1. K-means clustering is matrix factorization;bauckhage,2015
2. Laplacian Regularized Low-Rank Representation and Its Applications
3. Scalable Graph Topology Learning via Spectral Densification
4. Parallel Spectral Clustering in Distributed Systems
5. Scalable Sequential Spectral Clustering
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