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JMLR
2010
137views more  JMLR 2010»
15 years 1 months ago
Covariance in Unsupervised Learning of Probabilistic Grammars
Probabilistic grammars offer great flexibility in modeling discrete sequential data like natural language text. Their symbolic component is amenable to inspection by humans, while...
Shay B. Cohen, Noah A. Smith
JMLR
2010
140views more  JMLR 2010»
15 years 1 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
JMLR
2010
125views more  JMLR 2010»
15 years 1 months ago
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra
JMLR
2010
169views more  JMLR 2010»
15 years 1 months ago
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images
Deep belief nets have been successful in modeling handwritten characters, but it has proved more difficult to apply them to real images. The problem lies in the restricted Boltzma...
Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E....
JMLR
2010
184views more  JMLR 2010»
15 years 1 months ago
Sequential Monte Carlo Samplers for Dirichlet Process Mixtures
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
Yener Ülker, Bilge Günsel, Ali Taylan Ce...
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