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JMLR
2010
132views more  JMLR 2010»
13 years 4 months ago
On the Impact of Kernel Approximation on Learning Accuracy
Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
Corinna Cortes, Mehryar Mohri, Ameet Talwalkar
JMLR
2010
155views more  JMLR 2010»
13 years 8 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
PR
2008
169views more  PR 2008»
13 years 9 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
UAI
2004
13 years 11 months ago
On-line Prediction with Kernels and the Complexity Approximation Principle
The paper describes an application of Aggregating Algorithm to the problem of regression. It generalizes earlier results concerned with plain linear regression to kernel technique...
Alexander Gammerman, Yuri Kalnishkan, Vladimir Vov...
IPPS
2006
IEEE
14 years 3 months ago
On-the-fly kernel updates for high-performance computing clusters
High-performance computing clusters running longlived tasks currently cannot have kernel software updates applied to them without causing system downtime. These clusters miss oppo...
Kristis Makris, Kyung Dong Ryu