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144
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JMLR
2011
148views more  JMLR 2011»
14 years 10 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
122
Voted
ICCV
2007
IEEE
15 years 10 months ago
Support Kernel Machines for Object Recognition
Kernel classifiers based on Support Vector Machines (SVM) have recently achieved state-of-the art results on several popular datasets like Caltech or Pascal. This was possible by...
Ankita Kumar, Cristian Sminchisescu
121
Voted
PKDD
2009
Springer
147views Data Mining» more  PKDD 2009»
15 years 10 months ago
Kernel Polytope Faces Pursuit
Abstract. Polytope Faces Pursuit (PFP) is a greedy algorithm that approximates the sparse solutions recovered by 1 regularised least-squares (Lasso) [4,10] in a similar vein to (Or...
Tom Diethe, Zakria Hussain
146
Voted
PAMI
2010
337views more  PAMI 2010»
15 years 2 months ago
Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Kwang In Kim, Younghee Kwon
151
Voted
ICASSP
2011
IEEE
14 years 7 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor