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FOCM
2006
97views more  FOCM 2006»
13 years 8 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
TWC
2010
13 years 2 months ago
Indoor localization with channel impulse response based fingerprint and nonparametric regression
Abstract--In this paper, we propose a fingerprint-based localization scheme that exploits the location dependency of the channel impulse response (CIR). We approximate the CIR by a...
Yunye Jin, Wee-Seng Soh, Wai-Choong Wong
TSMC
2008
99views more  TSMC 2008»
13 years 7 months ago
Robust Regularized Kernel Regression
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
ICIP
2008
IEEE
14 years 2 months ago
Spatio-temporal video interpolation and denoising using motion-assisted steering kernel (MASK) regression
In this paper, we extend a (2-D) data-adaptive steering kernel regression framework for image processing to a (3-D) spatio-temporal framework for processing video. In particular, ...
Hiroyuki Takeda, Peter van Beek, Peyman Milanfar
NIPS
2003
13 years 9 months ago
Sequential Bayesian Kernel Regression
We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...
Jaco Vermaak, Simon J. Godsill, Arnaud Doucet