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» On regularization algorithms in learning theory
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149
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IJON
1998
158views more  IJON 1998»
15 years 4 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu
129
Voted
ALT
2006
Springer
16 years 1 months ago
Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice
Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
Hsuan-Tien Lin, Ling Li
ICML
2010
IEEE
15 years 5 months ago
Efficient Selection of Multiple Bandit Arms: Theory and Practice
We consider the general, widely applicable problem of selecting from n real-valued random variables a subset of size m of those with the highest means, based on as few samples as ...
Shivaram Kalyanakrishnan, Peter Stone
ICIP
2004
IEEE
16 years 6 months ago
Regularization studies on LDA for face recognition
It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 11 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang