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JCST
2010
139views more  JCST 2010»
13 years 5 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen
ACL
2009
13 years 5 months ago
Unsupervised Multilingual Grammar Induction
We investigate the task of unsupervised constituency parsing from bilingual parallel corpora. Our goal is to use bilingual cues to learn improved parsing models for each language ...
Benjamin Snyder, Tahira Naseem, Regina Barzilay
CMPB
2010
171views more  CMPB 2010»
13 years 2 months ago
Metabolica: A statistical research tool for analyzing metabolic networks
Steady state flux balance analysis (FBA) for cellular metabolism is used, e.g., to seek information on the activity of the different pathways under equilibrium conditions, or as a...
Jenni Heino, Daniela Calvetti, Erkki Somersalo
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
JMLR
2010
202views more  JMLR 2010»
13 years 2 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...