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Predictive Distribution Matching SVM for Multi-domain Learning
[chapter]
2010
Lecture Notes in Computer Science
Domain adaptation (DA) using labeled data from related source domains comes in handy when the labeled patterns of a target domain are scarce. Nevertheless, it is worth noting that when the predictive distribution P (y|x) of the domains differs, which establishes Negative Transfer [19] , DA approaches generally fail to perform well. Taking this cue, the Predictive Distribution Matching SVM (PDM-SVM) is proposed to learn a robust classifier in the target domain (referred to as the target
doi:10.1007/978-3-642-15880-3_21
fatcat:gs55ty53cjdmdghdi3vibr7zae