219 search results - page 8 / 44 » Learning the Dimensionality of Hidden Variables |
NIPS
2008
14 years 9 days 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...
COLT
1994
Springer
14 years 3 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...
SSPR
2010
Springer
13 years 9 months 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...
DAGM
2010
Springer
13 years 12 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...
JMLR
2012
12 years 1 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 ...