Robust sparse rank learning for non-smooth ranking measures

Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Volumn , Issue , 2009, Pages 259-266

  Sun, Zhengya ^a   Qin, Tao ^b   Tao, Qing ^a   Wang, Jue ^a  

^a INSTITUTE OF AUTOMATION   (China)

^b MICROSOFT RESEARCH ASIA   (China)

Author keywords

Information retrieval; Learn to rank; RSRank; Truncated gradient

Indexed keywords

BASELINE METHODS; GRADIENT DESCENT; LEARNING MODELS; LEARNING TO RANK; LOSS FUNCTIONS; NON-SMOOTH; NOVEL ALGORITHM; PAIRWISE CLASSIFICATION; PERFORMANCE GUARANTEES; RANK LEARNING; RANKING MEASURES; RANKING MODEL; SPARSE ALGORITHMS;

ALGORITHMS; INFORMATION SERVICES;

INFORMATION RETRIEVAL;

EID: 72449180896     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1571941.1571987     Document Type: Conference Paper

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