Subquadratic approximation algorithms for clustering problems in high dimensional spaces

Machine Learning

Volumn 56, Issue 1-3, 2004, Pages 153-167

  Borodin, Allan ^a   Ostrovsky, Rafail ^b   Rabani, Yuval ^c  

^a UNIVERSITY OF TORONTO   (Canada)

^b University of California   (United States)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

Graph theoretic clustering; High dimensional spaces; Sparse partitions

Indexed keywords

GRAPH-THEORITIC CLUSTERING; HIGH DIMENSIONAL SPACES; SPARSE PARTITIONS; SUBQUADRATIC APPROXIMATIONS;

ALGORITHMS; APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; COMPUTER VISION; DATA ACQUISITION; DATA MINING; DATABASE SYSTEMS; GEOGRAPHIC INFORMATION SYSTEMS; HEURISTIC METHODS; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; PATTERN RECOGNITION; SEARCH ENGINES; STATISTICAL METHODS; TRAVELING SALESMAN PROBLEM; VECTORS;

LEARNING SYSTEMS;

EID: 3142700648     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:MACH.0000033118.09057.80     Document Type: Article

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