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NIPS
2007
13 years 11 months ago
Learning Bounds for Domain Adaptation
Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
NIPS
2001
13 years 11 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
AAAI
1998
13 years 11 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
AUTOMATICA
2006
166views more  AUTOMATICA 2006»
13 years 10 months ago
On admissible pairs and equivalent feedback - Youla parameterization in iterative learning control
This paper revisits a well-known synthesis problem in iterative learning control, where the objective is to optimize a performance criterion over a class of causal iterations. The...
Mark Verwoerd, Gjerrit Meinsma, Theo de Vries
JSW
2007
147views more  JSW 2007»
13 years 10 months ago
Towards Secure e-Learning Applications: a Multiagent Platform
—This paper presents some results in the intersection of three technological fields: e-learning, multiagent systems, and standards to improve the development of secure systems. T...
Carine G. Webber, Maria de Fátima Webber do...