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» Learning with Transformation Invariant Kernels
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134
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JMLR
2008
131views more  JMLR 2008»
15 years 1 months ago
On Relevant Dimensions in Kernel Feature Spaces
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
124
Voted
NIPS
1997
15 years 3 months ago
Just One View: Invariances in Inferotemporal Cell Tuning
In macaque inferotemporal cortex (IT), neurons have been found to respond selectively to complex shapes while showing broad tuning (“invariance”) with respect to stimulus tran...
Maximilian Riesenhuber, Tomaso Poggio
117
Voted
JMLR
2008
95views more  JMLR 2008»
15 years 1 months ago
Learning Similarity with Operator-valued Large-margin Classifiers
A method is introduced to learn and represent similarity with linear operators in kernel induced Hilbert spaces. Transferring error bounds for vector valued large-margin classifie...
Andreas Maurer
115
Voted
ICPR
2008
IEEE
15 years 8 months ago
Regularized discriminant analysis for transformation-invariant object recognition
We present a novel method for incorporating prior knowledge about invariances in object recognition for discriminant analysis. In contrast to conventional isotropic regularization...
Yung-Kyun Noh, Jihun Ham, Daniel D. Lee
93
Voted
PKDD
2009
Springer
103views Data Mining» more  PKDD 2009»
15 years 8 months ago
Kernels for Periodic Time Series Arising in Astronomy
Abstract. We present a method for applying machine learning algorithms to the automatic classification of astronomy star surveys using time series of star brightness. Currently su...
Gabriel Wachman, Roni Khardon, Pavlos Protopapas, ...