6709 search results - page 442 / 1342 » Impacting the Learning Experience |
213
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ICML
2009
IEEE
16 years 8 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...
198
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ICML
2007
IEEE
16 years 8 months ago
2007
IEEE
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
208
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ICML
2007
IEEE
16 years 8 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
216
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ICML
2004
IEEE
16 years 8 months ago
2004
IEEE
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...
210
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ICML
2004
IEEE
16 years 8 months ago
2004
IEEE
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...