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» Structural Modelling with Sparse Kernels
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CVPR
2010
IEEE
14 years 10 months ago
Robust RVM regression using sparse outlier model
Kernel regression techniques such as Relevance Vector Machine (RVM) regression, Support Vector Regression and Gaussian processes are widely used for solving many computer vision p...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
TSMC
2010
14 years 4 months ago
Probability Density Estimation With Tunable Kernels Using Orthogonal Forward Regression
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Sheng Chen, Xia Hong, Chris J. Harris
GLOBECOM
2008
IEEE
15 years 4 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
SPLC
2010
14 years 11 months ago
Evolution of the Linux Kernel Variability Model
Abstract. Understanding the challenges faced by real projects in evolving variability models, is a prerequisite for providing adequate support for such undertakings. We study the e...
Rafael Lotufo, Steven She, Thorsten Berger, Krzysz...
JMLR
2008
110views more  JMLR 2008»
14 years 9 months ago
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...
Matthias W. Seeger