1419 search results - page 91 / 284 » Approximation Methods for Supervised Learning |
115
Voted
ICONIP
2007
15 years 1 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 ...
92
Voted
ML
2010
ACM
14 years 11 months 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 ...
115
Voted
SIGIR
2009
ACM
15 years 7 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...
106
Voted
CORR
2010
Springer
15 years 17 days ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
123
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ICML
2007
IEEE
16 years 1 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...