A theory of learning from different domains

Machine Learning

Volumn 79, Issue 1-2, 2010, Pages 151-175

  Ben David, Shai ^a   Blitzer, John ^b   Crammer, Koby ^c   Kulesza, Alex ^d   Pereira, Fernando ^e   Vaughan, Jennifer Wortman ^f  

^a UNIVERSITY OF WATERLOO   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^d UNIVERSITY OF PENNSYLVANIA   (United States)

^e GOOGLE INC   (United States)

^f HARVARD UNIVERSITY   (United States)

Author keywords

Domain adaptation; Learning theory; Sample selection bias; Transfer learning

Indexed keywords

ARTIFICIAL INTELLIGENCE; SOFTWARE ENGINEERING;

CONVEX COMBINATIONS; DIFFERENT DISTRIBUTIONS; DISCRIMINATIVE LEARNING; DOMAIN ADAPTATION; LABELED TRAINING DATA; LEARNING THEORY; SAMPLE-SELECTION BIAS; TRANSFER LEARNING;

ERRORS;

EID: 84897573740     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-009-5152-4     Document Type: Article

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