Introduction To The Analysis Of Algorithms (Fourth Edition)
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A01=Michael Soltys-kulinicz
Algorithm Analysis
Algorithm Correctness
Algorithm Design
Algorithms Textbook
Author_Michael Soltys-kulinicz
Category=UMB
Computational Complexity
Computer Science Algorithms
Computer Science Textbook
Data Structures Algorithms
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Machine Learning Algorithms
Programming Algorithms
Product details
- ISBN 9789819823512
- Publication Date: 05 Mar 2026
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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An Introduction to the Analysis of Algorithms is a comprehensive textbook that presents the fundamental methods for designing and analyzing computational algorithms through rigorous mathematical frameworks and practical implementation guidance. The book systematically explores major algorithmic paradigms including greedy algorithms, divide and conquer, dynamic programming, online algorithms, randomized algorithms, and parallel algorithms in linear algebra, providing detailed analysis of correctness and performance for each approach.The text emphasizes algorithm design techniques and formal analysis using pre/post-conditions and loop invariants, while covering essential computational foundations including automata theory, regular expressions, and complexity analysis. A new chapter on machine learning introduces students to this rapidly growing field, covering both supervised learning methods like regression and classification, and unsupervised techniques such as clustering, providing a bridge between traditional algorithmic thinking and modern data-driven approaches. The book also addresses practical considerations such as algorithm implementation, optimization techniques, and real-world applications across various domains.Intended for undergraduate and graduate students in computer science and mathematics, the self-contained presentation includes all necessary background material, worked examples, and extensive problem sets, making it suitable as both a classroom textbook and a comprehensive reference for anyone seeking to master algorithmic problem-solving and analysis.
