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» Approximate algorithms for neural-Bayesian approaches
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TSP
2011
230views more  TSP 2011»
14 years 4 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
JISE
2010
144views more  JISE 2010»
14 years 4 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
JMLR
2010
145views more  JMLR 2010»
14 years 4 months ago
Kernel Partial Least Squares is Universally Consistent
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
Gilles Blanchard, Nicole Krämer
TOG
2010
64views more  TOG 2010»
14 years 4 months ago
K-set tilable surfaces
This paper introduces a method for optimizing the tiles of a quadmesh. Given a quad-based surface, the goal is to generate a set of K quads whose instances can produce a tiled sur...
Chi-Wing Fu, Chi-Fu Lai, Ying He 0001, Daniel Cohe...
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...