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 John Morris
The text focuses on data structures and algorithms for manipulating them. Data structures for storing information in tables, lists, trees, queues and stacks are covered. Some basic graph and discrete transform algorithms are also discussed.
by Wolfgang Merkle - ESSLLI
The first part of the course gives an introduction to randomized algorithms and to standard techniques for their derandomization. The second part presents applications of the probabilistic method to the construction of logical models.
by Andrew Tridgell - samba.org
This thesis presents efficient algorithms for parallel sorting and remote data update. The sorting algorithms approach the problem by concentrating first on efficient but incorrect algorithms followed by a cleanup phase that completes the sort.
by Brad Miller, David Ranum - Franklin, Beedle & Associates
This textbook is designed as a text for a first course on data structures and algorithms, taught as the second course in the computer science curriculum. We cover abstract data types and data structures, writing algorithms, and solving problems.