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» The Kernel Trick for Distances
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ICPR
2008
IEEE
14 years 8 months ago
Kernel oriented discriminant analysis for speaker-independent phoneme spaces
Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
Heeyoul Choi, Ricardo Gutierrez-Osuna, Seungjin Ch...
PR
2006
93views more  PR 2006»
13 years 7 months ago
Learning the kernel parameters in kernel minimum distance classifier
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the per...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ICML
2010
IEEE
13 years 8 months ago
Fast Neighborhood Subgraph Pairwise Distance Kernel
We introduce a novel graph kernel called the Neighborhood Subgraph Pairwise Distance Kernel. The kernel decomposes a graph into all pairs of neighborhood subgraphs of small radius...
Fabrizio Costa, Kurt De Grave
NIPS
2003
13 years 9 months ago
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Liva Ralaivola, Florence d'Alché-Buc
TSP
2008
89views more  TSP 2008»
13 years 7 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe