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» Learning and Generalization with the Information Bottleneck
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ICIP
2006
IEEE
16 years 8 months ago
Local Discriminant Embedding with Tensor Representation
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...
Jian Xia, Dit-Yan Yeung, Guang Dai
ICML
1999
IEEE
16 years 7 months ago
Making Better Use of Global Discretization
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Eibe Frank, Ian H. Witten
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Real-time ranking with concept drift using expert advice
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
Hila Becker, Marta Arias
SIGITE
2006
ACM
16 years 18 days ago
Does a virtual networking laboratory result in similar student achievement and satisfaction?
Delivery of content in networking and system administration curricula involves significant hands-on laboratory experience supplementing traditional classroom instruction at the Ro...
Edith A. Lawson, William Stackpole
ECAI
2000
Springer
15 years 11 months ago
Naive Bayes and Exemplar-based Approaches to Word Sense Disambiguation Revisited
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...
Gerard Escudero, Lluís Màrquez, Germ...