Structured metric learning for high dimensional problems

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2008, Pages 195-203

  Davis, Jason V ^a   Dhillon, Inderjit S ^a  

^a University of Texas at Austin   (United States)

Author keywords

Algorithms; Experimentation

Indexed keywords

BASELINE METHODS; COLLABORATIVE FILTERING; DATA MINING APPLICATIONS; DATA SETS; DISTANCE FUNCTIONS; DISTANCE METRIC LEARNING; DOMAIN SPECIFICS; EXPERIMENTATION; HIGH-DIMENSIONAL; HIGH-DIMENSIONAL PROBLEMS; K-MEANS CLUSTERING; LATENT SEMANTIC ANALYSIS; LOW DIMENSIONAL; MAHALANOBIS DISTANCES; MATRIXES; METRIC LEARNING; NEAREST NEIGHBOR CLASSIFICATIONS; NEAREST NEIGHBOR SEARCHES; SEMI-SUPERVISED; STATISTICAL SOFTWARES; TECHNICAL CONTRIBUTIONS;

EDUCATION; INFORMATION THEORY; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS; MINING; OPTIMIZATION;

LEARNING ALGORITHMS;

EID: 65449163521     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1401890.1401918     Document Type: Conference Paper

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