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» Estimating Predictive Variances with Kernel Ridge Regression
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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
DAGM
2006
Springer
15 years 1 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
HAIS
2010
Springer
14 years 11 months ago
Power Prediction in Smart Grids with Evolutionary Local Kernel Regression
Electric grids are moving from a centralized single supply chain towards a decentralized bidirectional grid of suppliers and consumers in an uncertain and dynamic scenario. Soon, t...
Oliver Kramer, Benjamin Satzger, Jörg Lä...
ICASSP
2011
IEEE
14 years 1 months ago
Motion vector recovery with Gaussian Process Regression
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...
Hadi Asheri, Abdolkhalegh Bayati, Hamid R. Rabiee,...
ESEM
2008
ACM
14 years 11 months ago
A constrained regression technique for cocomo calibration
Building cost estimation models is often considered a search problem in which the solver should return an optimal solution satisfying an objective function. This solution also nee...
Vu Nguyen, Bert Steece, Barry W. Boehm