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167
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ICML
2000
IEEE
16 years 7 months ago
2000
IEEE
Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
169
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KDD
2007
ACM
16 years 7 months ago
2007
ACM
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
188
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ICML
2009
IEEE
16 years 1 months ago
2009
IEEE
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
161
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IPPS
2008
IEEE
16 years 1 months ago
2008
IEEE
In this study, we propose a new machine learning model namely, Adaptive Locality-Effective Kernel Machine (Adaptive-LEKM) for protein phosphorylation site prediction. Adaptive-LEK...
167
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MMM
2007
Springer
16 years 27 days ago
2007
Springer
This paper investigates the problem of learning the visual semantics of keyword categories for automatic image annotation. Supervised learning algorithms which learn only a single ...