Nonnegative matrix factorization for clustering

Nonnegative matrix factorization for clustering

This dissertation shows that nonnegative matrix factorization (NMF) can be extended to a general and efficient clustering method. Clustering is one of the fundamental tasks in machine learning. It is useful for unsupervised knowledge discovery in a variety of applications such as text mining and gen...

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Bibliographic Details
Main Author: Kuang, Da
Other Authors: Park, Haesun
Format: Others
Language:en_US
Published: Georgia Institute of Technology 2014
Subjects:
Nonnegative matrix factorization
Cluster analysis
Hierarchical clustering
Cancer subtype discovery
GPU computing
Sparse matrix multiplication
Online Access:http://hdl.handle.net/1853/52299

Internet

http://hdl.handle.net/1853/52299

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