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» Learning with Idealized Kernels
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NIPS
2007
13 years 11 months ago
Learning with Transformation Invariant Kernels
This paper considers kernels invariant to translation, rotation and dilation. We show that no non-trivial positive definite (p.d.) kernels exist which are radial and dilation inv...
Christian Walder, Olivier Chapelle
NN
2010
Springer
189views Neural Networks» more  NN 2010»
13 years 4 months ago
Sparse kernel learning with LASSO and Bayesian inference algorithm
Kernelized LASSO (Least Absolute Selection and Shrinkage Operator) has been investigated in two separate recent papers (Gao et al., 2008) and (Wang et al., 2007). This paper is co...
Junbin Gao, Paul W. Kwan, Daming Shi
ALT
2001
Springer
14 years 6 months ago
Learning of Boolean Functions Using Support Vector Machines
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
Ken Sadohara
ICCV
2009
IEEE
13 years 7 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
ASPLOS
2009
ACM
14 years 10 months ago
Maximum benefit from a minimal HTM
A minimal, bounded hardware transactional memory implementation significantly improves synchronization performance when used in an operating system kernel. We add HTM to Linux 2.4...
Owen S. Hofmann, Christopher J. Rossbach, Emmett W...