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» Sampling Techniques for Kernel Methods
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MLG
2007
Springer
15 years 3 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
ECCV
2002
Springer
15 years 11 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
15 years 4 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
WSCG
2000
132views more  WSCG 2000»
14 years 11 months ago
Adaptive Filtering for Progressive Monte Carlo Image Rendering
Image filtering is often applied as a post-process to Monte Carlo generated pictures, in order to reduce noise. In this paper we present an algorithm based on density estimation t...
Frank Suykens, Yves D. Willems
ICPR
2008
IEEE
15 years 4 months ago
Image sampling for localization using entropy
This paper introduces a robust adaptive patches sampling technique. The method does not rely on the use of keypoints to extract local information but all information contained in ...
Loic Lacheze, Ryad Benosman