1419 search results - page 91 / 284 » Approximation Methods for Supervised Learning |
131
Voted
ICONIP
2007
15 years 3 months ago
2007
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
104
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ML
2010
ACM
15 years 20 days ago
2010
ACM
When only a small number of labeled samples are available, supervised dimensionality reduction methods tend to perform poorly due to overfitting. In such cases, unlabeled samples ...
132
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SIGIR
2009
ACM
15 years 8 months ago
2009
ACM
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
128
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CORR
2010
Springer
15 years 2 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
137
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ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...