Logo

Randomized Algorithms by Wolfgang Merkle

Small book cover: Randomized Algorithms

Randomized Algorithms
by

Publisher: ESSLLI
Number of pages: 46

Description:
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 and briefly discusses related issues such as Rado-graphs and 0-1 laws.

Home page url

Download or read it online for free here:
Download link
(370KB, PDF)

Similar books

Book cover: Average Case Analysis of Algorithms on SequencesAverage Case Analysis of Algorithms on Sequences
by - Wiley-Interscience
A book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms.
(7567 views)
Book cover: A Practical Introduction to Data Structures and Algorithm AnalysisA Practical Introduction to Data Structures and Algorithm Analysis
by - Virginia Tech
A comprehensive treatment of fundamental data structures and algorithm analysis with a focus on how to create efficient data structures and algorithms. Aims to help the reader gain an understanding of how to select or design the best data structure.
(8250 views)
Book cover: LEDA: A Platform for Combinatorial and Geometric ComputingLEDA: A Platform for Combinatorial and Geometric Computing
by - Cambridge University Press
The book treats the architecture, the implementation, and the use of the LEDA system. LEDA is a library of efficient data types and algorithms and a platform for combinatorial and geometric computing, written in C++ and freely available worldwide.
(5344 views)
Book cover: Algorithms for Clustering DataAlgorithms for Clustering Data
by - 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.
(13529 views)