Semi-supervised hashing for large-scale search

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 12, 2012, Pages 2393-2406

  Wang, Jun ^a   Kumar, Sanjiv ^b   Chang, Shih Fu ^c  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b GOOGLE INC   (United States)

^c Columbia University ^*  (United States)

Author keywords

Binary codes; Hashing; Nearest neighbor search; Pairwise labels; Semi supervised hashing; Sequential hashing

Indexed keywords

APPROXIMATE NEAREST NEIGHBOR; EMPIRICAL ERRORS; HASHING; HASHING METHOD; HASHING TECHNIQUES; LABELED DATA; LARGE DATASETS; LOCALITY SENSITIVE HASHING; MEMORY EFFICIENCY; NEAREST NEIGHBOR SEARCH; NON-ORTHOGONAL; OVERFITTING; REGULARIZER; SEMANTIC SIMILARITY; SEMI-SUPERVISED; SEQUENTIAL HASHING; SEQUENTIAL LEARNING;

BINARY CODES; HASH FUNCTIONS; IMAGE RETRIEVAL; INFORMATION THEORY; INTERNET PROTOCOLS;

COMPUTATIONAL EFFICIENCY;

EID: 84865410773     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.48     Document Type: Article

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