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The work is incomplete and this account of it rougher than it might be. Such virtues as it has owe much to others; the faults are all mine. Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic appr.

http://school97ufa.ru/cache/map13.php This book is a comprehensive and accessible introduction to the cross-entropy CE method. The CE method started life around when the first author proposed an adaptive algorithm for rare-event simulation using a cross-entropy minimization …. Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo …. In the fall of , I was asked to teach a course on computer intrusion detection for the Department of Mathematical Sciences of The Johns Hopkins University.

That course was the genesis of this book. I had been working in the field for several ….

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Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to ….

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The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign In.

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