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19984448
Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
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Item #:
19984448
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Product Details
- Comprehensively covers randomization and probabilistic techniques in modern computer science
- Includes new material relevant to machine learning and big data analysis
- Requires only an elementary background in discrete mathematics
- Authored by Michael Mitzenmacher, a Professor of Computer Science at Harvard University, and Eli Upfal, a Professor of Computer Science at Brown University
- Michael 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
- Eli Upfal's main research interests are randomized algorithms, probabilistic analysis of algorithms, and computational statistics, with applications ranging from combinatorial and stochastic optimization, massive data analysis and sampling complexity to computational biology, and computational finance
| Publisher | Cambridge University Press |
| Publication date | July 3, 2017 |
| Edition | 2nd |
| Language | English |
| Print length | 484 pages |
| ISBN-10 | 9781107154889 |
| ISBN-13 | 978-1107154889 |
| Item Weight | 2.54 pounds (1.15 kg) |
| Dimensions | 10.27 x 7.45 x 1.15 inches (26.1 x 18.9 x 2.9 cm) |
Product Description
Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis
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Pros
- Comprehensive coverage of topics
- Clear explanations and examples
- Strong focus on algorithms
- Useful for both students and professionals
- Well-structured for easy understanding
Cons
- Occasional complex terminology
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