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JIFS
2008
155views more  JIFS 2008»
13 years 7 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...
IPPS
2000
IEEE
14 years 1 days ago
Transient Analysis of Dependability/Performability Models by Regenerative Randomization with Laplace Transform Inversion
In this paper we develop a variant of a previously proposed method the regenerative randomization method for the transient analysis of dependability performability models. The va...
Juan A. Carrasco
SPAA
1992
ACM
13 years 11 months ago
Separator Based Parallel Divide and Conquer in Computational Geometry
An O(log n) time, n processor randomized algorithm for computing the k-nearest neighbor graph of n points in d dimensions, for fixed d and k is presented. The method is based on t...
Alan M. Frieze, Gary L. Miller, Shang-Hua Teng
ISSAC
2007
Springer
132views Mathematics» more  ISSAC 2007»
14 years 1 months ago
Adaptive loops with kaapi on multicore and grid: applications in symmetric cryptography
The parallelization of two applications in symmetric cryptography is considered: block ciphering and a new method based on random sampling for the selection of basic substitution ...
Vincent Danjean, Roland Gillard, Serge Guelton, Je...
BMCBI
2007
147views more  BMCBI 2007»
13 years 7 months ago
Bias in random forest variable importance measures: Illustrations, sources and a solution
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...
Carolin Strobl, Anne-Laure Boulesteix, Achim Zeile...