1972 search results - page 101 / 395 » Hidden semi-Markov models |
194
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JMLR
2012
13 years 8 months ago
2012
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
160
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NIPS
2007
15 years 7 months ago
2007
The learning of probabilistic models with many hidden variables and nondecomposable dependencies is an important and challenging problem. In contrast to traditional approaches bas...
186
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JMLR
2010
15 years 1 months ago
2010
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
182
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ECML
2005
Springer
15 years 12 months ago
2005
Springer
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
169
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NIPS
2000
15 years 7 months ago
2000
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...