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ALT
2009
Springer
15 years 10 months ago
Learning and Domain Adaptation
Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
Yishay Mansour
CVIU
2004
115views more  CVIU 2004»
15 years 6 months ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
ALIFE
2010
15 years 5 months ago
Modeling Social Learning of Language and Skills
We present a model of social learning of both language and skills, while assuming—insofar as possible—strict autonomy, virtual embodiment, and situatedness. This model is built...
Paul Vogt, Evert Haasdijk
CVPR
2010
IEEE
15 years 4 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
CVPR
2008
IEEE
16 years 8 months ago
Multiple-instance ranking: Learning to rank images for image retrieval
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Yang Hu, Mingjing Li, Nenghai Yu