This book constitutes the refereed proceedings of the 13th International Symposium on Static Analysis, SAS 2006. The book ...
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The book addresses all aspects of static analysis including abstract domains, abstract interpretation, abstract testing, ...
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The statistical analysis of extreme data is important for various disciplines, including hydrology, insurance, finance, engineering ...
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Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in ...
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Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the ...
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STATISTICAL MODELING AND ANALYSIS FOR COMPLEX DATA PROBLEMS treats some of today’s more complex problems and it reflects ...
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This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of ...
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The book develops the statistical approach to inverse problems with an emphasis on modeling and computations. The framework ...
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This book constitutes the refereed proceedings of the 4th International Symposium on Stochastic Algorithms: Foundations and ...
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Constitutes the refereed proceedings of the Third International Symposium on Stochastic Algorithms: Foundations and Applications, ...
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The behavior of many technical systems important in everyday life can be described using discrete states and state-changing ...
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Stochastic Dominance is devoted to investment decision-making under uncertainty. The book covers three basic approaches to ...
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The volume "Stochastic Geometry" contains the lectures given at the CIME summer school in Martina Franca in September 1974. ...
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This book presents the main methodological and theoretical developments in stochastic global optimization. The extensive ...
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STOCHASTIC LINEAR PROGRAMMING: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical ...
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The search for optimal solutions pervades our daily lives. From the scientific point of view, optimization procedures play ...
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Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., ...
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Optimization problems arising in practice involve random model parameters. For the computation of robust optimal solutions, ...
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Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers ...
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Stochastic geometry has in recent years experienced considerable progress, both in its applications to other sciences and ...
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