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» Optimal feature selection for support vector machines
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PR
2007
165views more  PR 2007»
13 years 7 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
CVPR
2011
IEEE
12 years 11 months ago
Support Tucker Machines
In this paper we address the two-class classification problem within the tensor-based framework, by formulating the Support Tucker Machines (STuMs). More precisely, in the propos...
Irene Kotsia, Ioannis Patras
ICML
2005
IEEE
14 years 8 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
SIGMOD
1999
ACM
110views Database» more  SIGMOD 1999»
14 years 5 days ago
Multi-dimensional Selectivity Estimation Using Compressed Histogram Information
The database query optimizer requires the estimation of the query selectivity to find the most efficient access plan. For queries referencing multiple attributes from the same rel...
Ju-Hong Lee, Deok-Hwan Kim, Chin-Wan Chung
MLDM
2007
Springer
14 years 2 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...