566 search results - page 37 / 114 » Approximation Spaces in Machine Learning and Pattern Recogni... |
130
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DAC
2003
ACM
16 years 4 months ago
2003
ACM
The use of Support Vector Machines (SVMs) to represent the performance space of analog circuits is explored. In abstract terms, an analog circuit maps a set of input design parame...
129
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GECCO
2008
Springer
15 years 4 months ago
2008
Springer
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
125
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ECCV
2000
Springer
16 years 5 months ago
2000
Springer
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
138
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ECML
2005
Springer
15 years 8 months ago
2005
Springer
Finding a point which minimizes the maximal distortion with respect to a dataset is an important estimation problem that has recently received growing attentions in machine learnin...
147
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COLT
1999
Springer
15 years 7 months ago
1999
Springer
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...