Stochastic Algorithms: Foundations and Applications: Second International Symposium, SAGA 2003, Hatfield, UK, September 22-23, 2003, Proceedings (Lecture Notes in Computer Science)
by Andreas Albrecht
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The second Symposium on Stochastic Algorithms, Foundations and Applications (SAGA 2003), took place on September 22-23,2003, in Hat'eld, England.The present volume comprises 12 contributed papers and 3 invited talks. The contributed papers included in the proceedings present results in the following areas: ant colony optimization; randomized algorithmsfor the intersection problem; - cal search for constraint satisfaction problems; randomized local search methods for combinatorial show more optimization, in particular, simulated annealing techniques; probabilistic global search algorithms; network communication complexity; open shop scheduling; aircraft routing; traf'c control; randomized straight-line programs; and stochastic - tomata and probabilistic transformations. TheinvitedtalkbyRolandKirschnerprovidesabriefintroductiontoquantuminf- matics. The requirements and the prospects of the physical implementation of a qu- tum computer are addressed. Lucila Ohno-Machado and Winston P. Kuo describe the factors that make the an- ysis of high-throughput gene expression data especially challenging, and indicate why properly evaluated stochastic algorithms can play a particularly important role in this process. John Vaccaro et al. review a fundamental element of quantum information theory, source coding, which entails the compression of quantum data. A recent experiment that demonstrates this fundamental principle is presented and discussed. Our special thanks go to all who supported SAGA 2003, to all authors who subm- ted papers, to the members of the program committee, to the invited speakers, and to the members of the organizing committee. Andreas Albrecht Kathleen Steinhofel ] Organization SAGA2003wasorganizedbytheUniversityofHertfordshire, DepartmentofComputer Science, Hat'eld, Hertfordshire AL10 9AB, United Kingdom. show lessTags
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