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» Approximation Methods for Supervised Learning
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CVPR
2010
IEEE
14 years 6 months ago
Efficient Additive Kernels via Explicit Feature Maps
Maji and Berg [13] have recently introduced an explicit feature map approximating the intersection kernel. This enables efficient learning methods for linear kernels to be applied...
Andrea Vedaldi, Andrew Zisserman
GECCO
2005
Springer
107views Optimization» more  GECCO 2005»
14 years 3 months ago
Investigating the success of spatial coevolution
We investigate the results of coevolution of spatially distributed populations. In particular, we describe work in which a simple function approximation problem is used to compare...
Nathan Williams, Melanie Mitchell
CORR
2010
Springer
253views Education» more  CORR 2010»
13 years 10 months ago
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCu...
NCA
2008
IEEE
13 years 10 months ago
Neurodynamic programming: a case study of the traveling salesman problem
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...
BMCBI
2010
111views more  BMCBI 2010»
13 years 10 months ago
Protein sequences classification by means of feature extraction with substitution matrices
Background: This paper deals with the preprocessing of protein sequences for supervised classification. Motif extraction is one way to address that task. It has been largely used ...
Rabie Saidi, Mondher Maddouri, Engelbert Mephu Ngu...