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» Sparse Kernel Regressors
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ICA
2007
Springer
13 years 10 months ago
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...
Ales Holobar, Damjan Zazula
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
Bayesian Generalized Kernel Models
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
SODA
2012
ACM
170views Algorithms» more  SODA 2012»
11 years 11 months ago
Compression via matroids: a randomized polynomial kernel for odd cycle transversal
The Odd Cycle Transversal problem (OCT) asks whether a given graph can be made bipartite by deleting at most k of its vertices. In a breakthrough result Reed, Smith, and Vetta (Op...
Stefan Kratsch, Magnus Wahlström
CVPR
2005
IEEE
14 years 10 months ago
Multiple Collaborative Kernel Tracking
Those motion parameters that cannot be recovered from image measurements are unobservable in the visual dynamic system. This paper studies this important issue of singularity in th...
Zhimin Fan, Ying Wu, Ming Yang
ICCV
2007
IEEE
14 years 10 months ago
Population Shape Regression From Random Design Data
Regression analysis is a powerful tool for the study of changes in a dependent variable as a function of an independent regressor variable, and in particular it is applicable to t...
Bradley C. Davis, P. Thomas Fletcher, Elizabeth Bu...