Titlebook: Stochastic Algorithms: Foundations and Applications; Second International Andreas Albrecht,Kathleen Steinhöfel Conference proceedings 2003

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Stochastic Algorithms: Foundations and ApplicationsSecond International

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过份艳丽

Optimality of Randomized Algorithms for the Intersection Problem,c algorithms for this problem, and offer lower bounds on the randomized complexity in different models (cost model, alternation model)..We refine the alternation model into the . to prove that randomized algorithms perform better than deterministic ones on the intersection problem. We present a rand

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Stochastic Algorithms for Gene Expression Analysis,sets, the number of variables exceeds the number of observations by at least one order of magnitude. Substantial variable reduction is usually necessary before learning algorithms can be utilized in practice. Commonly used greedy variable selection strategies preclude the discovery of potentially im

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embolus

Testing a Simulated Annealing Algorithm in a Classification Problem, which are generated and simulated by a Design of Experiments. This way, it is possible to find data characteristics that influence the relative classification performance of different classification methods. It turns out that the new method improves the classification performance of the classical L

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Global Search through Sampling Using a PDF,s space using a probability density function (PDF). The PDF is updated in four nested cycles such that the search focuses on regions containing good solutions without avoiding other regions altogether. Tests on benchmark problems having multi-parameter non-linear objective functions revealed that PG

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