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The book explores the fascinating world of randomized algorithms, which leverage randomness to solve computational problems more efficiently than deterministic methods. It covers fundamental concepts, techniques, and applications, providing a comprehensive overview of how randomness can simplify complex algorithms in areas such as optimization, data structures, and network design. Through detailed examples and theoretical insights, readers gain an understanding of both the power and limitations of these innovative algorithms, making it a valuable resource for computer scientists and mathematicians alike.
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Randomized Algorithms: Approximation, Generation, and Counting, Russ Bubley
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- Pubblicato
- 2011
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