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Probability and Computing
Randomization and Probabilistic Techniques in Algorithms and Data Analysis
Buch von Michael Mitzenmacher (u. a.)
Sprache: Englisch

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Beschreibung
This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.
This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.
Über den Autor
Michael Mitzenmacher is a Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University, Massachusetts. Professor Mitzenmacher has authored or co-authored over 200 conference and journal publications on a variety of topics, including algorithms for the internet, efficient hash-based data structures, erasure and error-correcting codes, power laws, and compression. His work on low-density parity-check codes shared the 2002 IEEE Information Theory Society Best Paper Award and won the 2009 ACM SIGCOMM Test of Time Award. He was elected as the Chair of the ACM Special Interest Group on Algorithms and Computation Theory in 2015.
Inhaltsverzeichnis
1. Events and probability; 2. Discrete random variables and expectations; 3. Moments and deviations; 4. Chernoff and Hoeffding bounds; 5. Balls, bins, and random graphs; 6. The probabilistic method; 7. Markov chains and random walks; 8. Continuous distributions and the Polsson process; 9. The normal distribution; 10. Entropy, randomness, and information; 11. The Monte Carlo method; 12. Coupling of Markov chains; 13. Martingales; 14. Sample complexity, VC dimension, and Rademacher complexity; 15. Pairwise independence and universal hash functions; 16. Power laws and related distributions; 17. Balanced allocations and cuckoo hashing.
Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 467
Inhalt: Gebunden
ISBN-13: 9781107154889
ISBN-10: 110715488X
Sprache: Englisch
Einband: Gebunden
Autor: Mitzenmacher, Michael
Upfal, Eli
Auflage: 2nd edition
Hersteller: Cambridge University Pr.
Abbildungen: 8 b/w illus. 1 table
Maße: 259 x 182 x 27 mm
Von/Mit: Michael Mitzenmacher (u. a.)
Erscheinungsdatum: 31.01.2017
Gewicht: 1,158 kg
preigu-id: 109575971
Über den Autor
Michael Mitzenmacher is a Professor of Computer Science in the School of Engineering and Applied Sciences at Harvard University, Massachusetts. Professor Mitzenmacher has authored or co-authored over 200 conference and journal publications on a variety of topics, including algorithms for the internet, efficient hash-based data structures, erasure and error-correcting codes, power laws, and compression. His work on low-density parity-check codes shared the 2002 IEEE Information Theory Society Best Paper Award and won the 2009 ACM SIGCOMM Test of Time Award. He was elected as the Chair of the ACM Special Interest Group on Algorithms and Computation Theory in 2015.
Inhaltsverzeichnis
1. Events and probability; 2. Discrete random variables and expectations; 3. Moments and deviations; 4. Chernoff and Hoeffding bounds; 5. Balls, bins, and random graphs; 6. The probabilistic method; 7. Markov chains and random walks; 8. Continuous distributions and the Polsson process; 9. The normal distribution; 10. Entropy, randomness, and information; 11. The Monte Carlo method; 12. Coupling of Markov chains; 13. Martingales; 14. Sample complexity, VC dimension, and Rademacher complexity; 15. Pairwise independence and universal hash functions; 16. Power laws and related distributions; 17. Balanced allocations and cuckoo hashing.
Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 467
Inhalt: Gebunden
ISBN-13: 9781107154889
ISBN-10: 110715488X
Sprache: Englisch
Einband: Gebunden
Autor: Mitzenmacher, Michael
Upfal, Eli
Auflage: 2nd edition
Hersteller: Cambridge University Pr.
Abbildungen: 8 b/w illus. 1 table
Maße: 259 x 182 x 27 mm
Von/Mit: Michael Mitzenmacher (u. a.)
Erscheinungsdatum: 31.01.2017
Gewicht: 1,158 kg
preigu-id: 109575971
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