Algorithms for Clustering Data
by Anil K. Jain, Richard C. Dubes
Publisher: Prentice Hall 1988
Number of pages: 334
This book will be useful for those in the scientific community who gather data and seek tools for analyzing and interpreting data. It will be a valuable reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.
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by Marko Petkovsek, Herbert S. Wilf, Doron Zeilberger - AK Peters, Ltd.
The book shows how some computer algorithms can simplify complex summations and if there is no such simplification they will prove this to be the case. The authors present the underlying mathematical theory, and the principle theorems and proofs.
by Donald E. Knuth - Addison-Wesley Professional
This work on the analysis of algorithms has long been recognized as the definitive description of classical computer science, arguably the most influential work ever written on computer programming. Volume 4 covers Combinatorial Algorithms.
by D. P. Williamson, D. B. Shmoys - Cambridge University Press
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. It is organized around techniques for designing approximation algorithms, including greedy and local search algorithms.
by Catherine Leung - GitBook
This book is a survey of several standard algorithms and data structures. It will also introduce the methodology used to perform a formal analysis of an algorithm so that the reason behind the different implementations can be better understood.