1622 search results - page 73 / 325 » Learning a Hidden Matching |
122
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GECCO
2007
Springer
15 years 9 months ago
2007
Springer
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
121
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CVPR
2007
IEEE
16 years 5 months ago
2007
IEEE
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
111
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IJCAI
1993
15 years 4 months ago
1993
One of the open problems listed in Rivest and Schapire, 1989] is whether and how that the copies of L in their algorithm can be combined into one for better performance. This pape...
137
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JMLR
2010
14 years 9 months ago
2010
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
129
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NN
1997
Springer
15 years 7 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...