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DMIN
2006
134views Data Mining» more  DMIN 2006»
14 years 11 months ago
Hyper-Rectangular and k-Nearest-Neighbor Models in Stochastic Discrimination
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
Iryna Skrypnyk, Tin Kam Ho
CORR
2006
Springer
94views Education» more  CORR 2006»
14 years 9 months ago
Fitness Uniform Optimization
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
Marcus Hutter, Shane Legg
RIVF
2007
14 years 11 months ago
Simple estimate of signal to interference ratio with randomly located antennas
— We consider a propagation model under path loss, shadowing and multipath effects, where each cell are a Voronoi tessellation and the generating points of this cells are a unifo...
Laurent Decreusefond, Eduardo Ferreir, Philippe Ma...
FOCS
1993
IEEE
15 years 1 months ago
Scale-sensitive Dimensions, Uniform Convergence, and Learnability
Learnability in Valiant’s PAC learning model has been shown to be strongly related to the existence of uniform laws of large numbers. These laws define a distribution-free conver...
Noga Alon, Shai Ben-David, Nicolò Cesa-Bian...
ENTCS
2008
95views more  ENTCS 2008»
14 years 9 months ago
Coverage-biased Random Exploration of Models
This paper describes a set of methods for randomly drawing traces in large models either uniformly among all traces, or with a coverage criterion as target. Classical random walk ...
Marie-Claude Gaudel, Alain Denise, Sandrine-Domini...