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NIPS
2007
13 years 9 months ago
On higher-order perceptron algorithms
A new algorithm for on-line learning linear-threshold functions is proposed which efficiently combines second-order statistics about the data with the ”logarithmic behavior” ...
Claudio Gentile, Fabio Vitale, Cristian Brotto
KBS
2006
150views more  KBS 2006»
13 years 7 months ago
Clusterer ensemble
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Zhi-Hua Zhou, Wei Tang
ICML
2005
IEEE
14 years 8 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
14 years 2 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard
ICALT
2006
IEEE
14 years 1 months ago
A Relationship between e-Learning Performance and Personality
This paper investigated whether learner’s personality features might have effects on uses of Web-based Hypermedia Systems, which has been used in the electronic learning (e-Lear...
Amal Al-Dujaily, Hokyoung Ryu