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» Flexible kernels for RBF networks
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IJCNN
2007
IEEE
15 years 6 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
ICANN
2001
Springer
15 years 4 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
NIPS
2003
15 years 1 months ago
Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression
Nonlinear filtering can solve very complex problems, but typically involve very time consuming calculations. Here we show that for filters that are constructed as a RBF network ...
Roland Vollgraf, Michael Scholz, Ian A. Meinertzha...
CONEXT
2008
ACM
15 years 1 months ago
Trellis: a platform for building flexible, fast virtual networks on commodity hardware
We describe Trellis, a platform for hosting virtual networks on shared commodity hardware. Trellis allows each virtual network to define its own topology, control protocols, and f...
Sapan Bhatia, Murtaza Motiwala, Wolfgang Mühl...
SAMOS
2004
Springer
15 years 5 months ago
A Novel Data-Path for Accelerating DSP Kernels
A high-performance data-path to implement DSP kernels is proposed in this paper. The data-path is based on a flexible, universal, and regular component to optimally exploiting both...
Michalis D. Galanis, George Theodoridis, Spyros Tr...