Average Case Analysis of Algorithms on Sequences
by Wojciech Szpankowski
Publisher: Wiley-Interscience 2001
Number of pages: 576
A timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume.
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by Jeff Erickson - University of Illinois at Urbana-Champaign
These are lecture notes, homework questions, and exam questions from algorithms courses the author taught at the University of Illinois. It is assumed that the reader has mastered the material covered in the first 2 years of a typical CS curriculum.
by Jurg Nievergelt, Klaus Hinrichs - Prentice Hall
Contents: Programming environments for motion, graphics, and geometry; Programming concepts - beyond notation; Objects, algorithms, programs; Complexity of problems and algorithms; Data structures; Interaction between algorithms and data structures.
by Jeffrey Scott Vitter - Now Publishers
The book describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, etc.
by Anil K. Jain, Richard C. Dubes - Prentice Hall
The book is useful for scientists who gather data and seek tools for analyzing and interpreting data. It will be a reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.