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» Graph based multi-modality learning
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ICML
2004
IEEE
14 years 8 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
14 years 2 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
HICSS
2003
IEEE
162views Biometrics» more  HICSS 2003»
14 years 28 days ago
Decision Support Models for Composing and Navigating through e-Learning Objects
Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways...
Gerhard Knolmayer
ICSE
2000
IEEE-ACM
13 years 11 months ago
Multibook's test environment
Well engineered Web based courseware and exercises provide flexibility and added value to the students, which goes beyond the traditional text book or CD-ROM based courses. The Mu...
Nathalie Poerwantoro, Abdulmotaleb El-Saddik, Bern...
NIPS
2007
13 years 9 months ago
Statistical Analysis of Semi-Supervised Regression
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
John D. Lafferty, Larry A. Wasserman