219 search results - page 8 / 44 » Learning the Dimensionality of Hidden Variables |
94
Voted
NIPS
2008
15 years 3 months ago
2008
In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
113
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COLT
1994
Springer
15 years 6 months ago
1994
Springer
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
139
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SSPR
2010
Springer
15 years 6 days ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
122
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DAGM
2010
Springer
15 years 2 months ago
2010
Springer
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
146
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JMLR
2012
13 years 4 months ago
2012
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...