An information-theoretic derivation of min-cut-based clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 6, 2010, Pages 988-995

  Raj, Anil ^a   Wiggins, Chris H ^a  

^a Department of Earth and Environmental Sciences   (United States)

Author keywords

Clustering; Graph diffusion.; Graphs; Information Bottleneck; Information theory; Min cut

Indexed keywords

COMMUNITY STRUCTURES; GENERATIVE MODEL; GRAPH DIFFUSION.; GRAPH PARTITIONING; HIGH PROBABILITY; INFORMATION BOTTLENECK; MIN-CUT; PREDICTIVE INFORMATION; RANDOM WALKERS; THEORETIC DERIVATION;

GRAPH THEORY; GRAPHIC METHODS; IMAGE SEGMENTATION; INFORMATION THEORY; OPTIMIZATION;

COST FUNCTIONS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; IMAGE PROCESSING; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; IMAGE PROCESSING, COMPUTER-ASSISTED;

EID: 77951578710     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2009.124     Document Type: Article

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