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» Learning the Dimensionality of Hidden Variables
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ICASSP
2008
IEEE
14 years 4 months ago
Maximum entropy relaxation for multiscale graphical model selection
We consider the problem of learning multiscale graphical models. Given a collection of variables along with covariance specifications for these variables, we introduce hidden var...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
BC
2004
65views more  BC 2004»
13 years 9 months ago
SINBAD: A neocortical mechanism for discovering environmental variables and regularities hidden in sensory input
We propose that a top priority of the cerebral cortex must be the discovery and explicit representation of the environmental variables that contribute as major factors to environme...
Oleg V. Favorov, Dan Ryder
JAIR
2008
164views more  JAIR 2008»
13 years 9 months ago
Gesture Salience as a Hidden Variable for Coreference Resolution and Keyframe Extraction
Gesture is a non-verbal modality that can contribute crucial information to the understanding of natural language. But not all gestures are informative, and non-communicative hand...
Jacob Eisenstein, Regina Barzilay, Randall Davis
PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
14 years 2 months ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
JMLR
2010
126views more  JMLR 2010»
13 years 4 months ago
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach
We propose a novel application of the Simultaneous Orthogonal Matching Pursuit (SOMP) procedure to perform variable selection in ultra-high dimensional multiple output regression ...
Mladen Kolar, Eric P. Xing