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NIPS
2000
15 years 1 months ago
Sparse Representation for Gaussian Process Models
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
Lehel Csató, Manfred Opper
104
Voted
NIPS
2000
15 years 1 months ago
From Margin to Sparsity
We present an improvement of Noviko 's perceptron convergence theorem. Reinterpreting this mistakebound as a margindependent sparsity guarantee allows us to give a PAC{style ...
Thore Graepel, Ralf Herbrich, Robert C. Williamson
NIPS
2000
15 years 1 months ago
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to novelty detection provide a measure of how...
Paul Hayton, Bernhard Schölkopf, Lionel Taras...
81
Voted
NIPS
2000
15 years 1 months ago
A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work
We investigate how the normalization of vectors influences the result of SVMs. 1 Normalization For the theoretical background, please refer to [1]. 2 Experiments We empirically co...
Ralf Herbrich, Thore Graepel
NIPS
2000
15 years 1 months ago
A Silicon Primitive for Competitive Learning
Competitive learning is a technique for training classification and clustering networks. We have designed and fabricated an 11transistor primitive, that we term an automaximizing ...
David Hsu, Miguel Figueroa, Chris Diorio