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» A Framework for Multiple-Instance Learning
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KDD
2008
ACM
183views Data Mining» more  KDD 2008»
16 years 4 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
ICML
2004
IEEE
16 years 4 months ago
Improving SVM accuracy by training on auxiliary data sources
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Pengcheng Wu, Thomas G. Dietterich
UAI
1997
15 years 5 months ago
Update Rules for Parameter Estimation in Bayesian Networks
This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [1...
Eric Bauer, Daphne Koller, Yoram Singer
ITS
1998
Springer
107views Multimedia» more  ITS 1998»
15 years 8 months ago
Toward a Unification of Human-Computer Learning and Tutoring
We define a learning tutor as being an intelligent agent that learns from human tutors and then tutors human learners. The notion of a learning tutor provides a conceptual framewor...
Henry Hamburger, Gheorghe Tecuci
CVPR
2008
IEEE
16 years 5 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