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» Structural Inference for Semistructured Data
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BMCBI
2008
124views more  BMCBI 2008»
14 years 10 months ago
Inferring modules of functionally interacting proteins using the Bond Energy Algorithm
Background: Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or struct...
Ryosuke Watanabe, Enrique Morett, Edgar E. Vallejo
CORR
2011
Springer
151views Education» more  CORR 2011»
14 years 5 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
NIPS
2003
14 years 11 months ago
Learning with Local and Global Consistency
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...
JMLR
2010
202views more  JMLR 2010»
14 years 4 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...
TSP
2010
14 years 4 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...