Learning from heterogeneous sources via gradient boosting consensus

Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012

Volumn , Issue , 2012, Pages 224-235

  Shi, Xiaoxiao ^a   Paiement, Jean Francois ^b   Grangier, David ^b   Yu, Philip S ^a,c  

^a 1120 Science and Engineering Offices   (United States)

^b AT AND T LABS RESEARCH   (United States)

^c KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; E-LEARNING; FORECASTING; SPACE DIVISION MULTIPLE ACCESS; STOCHASTIC SYSTEMS;

GENERAL OPTIMIZATIONS; HETEROGENEOUS SOURCES; MULTIPLE DATA SOURCES; MULTIPLE HETEROGENEOUS DATA SOURCE; NUMBER RECOGNITION; OBJECTIVE FUNCTIONS; OUT-OF-SAMPLE ERRORS; STOCHASTIC GRADIENT BOOSTING;

LEARNING SYSTEMS;

EID: 84880239829     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972825.20     Document Type: Conference Paper

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