9780521884273 - Concentration of Measure for the Analysis of Randomized Algorithms di Dubhashi, Devdatt P.; Panconesi, Alessandro (18 risultati)

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Hardcover. Condizione: Very Good. Bookplate, otherwise text clean and tight; no dust jacket; 8.90 X 6.10 X 0.90 inches; 214 pages.

Condizione: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned. Ex library copy with usual stamps & stickers.

Condizione: New.

Condizione: New.

Condizione: New. In.

Hardcover. Condizione: new. Hardcover. 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. This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condizione: Brand New. 1st edition. 248 pages. 8.90x6.10x0.90 inches. In Stock.

Condizione: New. pp. xiv + 196.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Condizione: New. pp. xiv + 196 12 Illus.

Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardcover. Condizione: Brand New. 1st edition. 248 pages. 8.90x6.10x0.90 inches. In Stock. This item is printed on demand.

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Hardcover. Condizione: new. Hardcover. 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. This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condizione: 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.Randomized algorithms have become a central part of the algorithms curriculum, based on their increasi.

Buch. Condizione: Neu. Concentration of Measure for the Analysis of Randomized Algorithms | Devdatt P. Dubhashi (u. a.) | Buch | Gebunden | Englisch | 2014 | Cambridge University Press | EAN 9780521884273 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condizione: new. Hardcover. 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 ChernoffHoeffding 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 ChernoffHoeffding 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. This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.