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» Sampling Techniques for Kernel Methods
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STOC
2010
ACM
245views Algorithms» more  STOC 2010»
15 years 2 months ago
Weighted Geometric Set Cover via Quasi-Uniform Sampling
There has been much progress on geometric set cover problems, but most known techniques only apply to the unweighted setting. For the weighted setting, very few results are known ...
Kasturi Varadarajan
TSP
2008
166views more  TSP 2008»
14 years 9 months ago
Nonuniform Sampling of Periodic Bandlimited Signals
Abstract--Digital processing techniques are based on representing a continuous-time signal by a discrete set of samples. This paper treats the problem of reconstructing a periodic ...
E. Margolis, Yonina C. Eldar
ICCV
2001
IEEE
15 years 11 months ago
Example-Based Facial Sketch Generation with Non-parametric Sampling
In this paper, we present an example-based facial sketch system. Our system automatically generates a sketch from an input image, by learning from example sketches drawn with a pa...
Hong Chen, Ying-Qing Xu, Heung-Yeung Shum, Song Ch...
ICCAD
2008
IEEE
107views Hardware» more  ICCAD 2008»
15 years 4 months ago
Importance sampled circuit learning ensembles for robust analog IC design
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
Peng Gao, Trent McConaghy, Georges G. E. Gielen
VALUETOOLS
2006
ACM
15 years 3 months ago
Splitting with weight windows to control the likelihood ratio in importance sampling
Importance sampling (IS) is the most widely used efficiency improvement method for rare-event simulation. When estimating the probability of a rare event, the IS estimator is the ...
Pierre L'Ecuyer, Bruno Tuffin