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Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff-Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff-Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians. Seller Inventory # LU-9781107606609
This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms.
About the Authors:
Devdatt P. Dubhashi is Professor in the Department of Computer Science and Engineering at Chalmers University, Sweden. He earned a Ph.D. in computer science from Cornell University and held positions at the Max-Planck-Institute for Computer Science in Saarbruecken, BRICS, the University of Aarhus and IIT Delhi. Dubhashi has published widely at international conferences and in journals, including many special issues dedicated to best contributions. His research interests span the range from combinatorics to probabilistic analysis of algorithms, and more recently, to computational systems biology and distributed information systems such as the Web.
Alessandro Panconesi is Professor of Computer Science at Sapienza University of Rome. He earned a Ph.D. in computer science from Cornell University and is the recipient of the 1992 ACM Danny Lewin Award. Panconesi has published more than 50 papers in international journals and selective conference proceedings and he is the associate editor of the Journal of Discrete Algorithms and the director of BiCi, the Bertinoro International Center of Informatics. His research spans areas of algorithmic research as diverse as randomized algorithms, distributed computing, complexity theory, experimental algorithmics, wireless networking and Web information retrieval.
Title: Concentration of Measure for the Analysis of...
Publisher: Cambridge University Press, GB
Publication Date: 2012
Binding: Paperback
Condition: New
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms.Über den AutorDevdatt P. Dubhashi is Professor in the Department of Computer Scie. Seller Inventory # 447220677
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Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Concentration of Measure for the Analysis of Randomized Algorithms | Devdatt P. Dubhashi (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2012 | Cambridge University Press | EAN 9781107606609 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. Seller Inventory # 108028041
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