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'This text provides a solid background in probabilistic techniques, illustrating each with well-chosen examples. The explanations are clear, and convey the intuition behind the results and techniques, yet the coverage is rigorous. An excellent advanced undergraduate text.' Peter Bartlett, Professor of Computer Science, University of California, Berkeley
'This book is suitable as a text for upper division undergraduates and first year graduate students in computer science and related disciplines. It will also be useful as a reference for researchers who would like to incorporate these tools into their work. I enjoyed teaching from the book and highly recommend it.' Valerie King, Professor of Computer Science, University of Victoria, British Columbia
'Buy it, read it, enjoy it; profit from it. it feels as if it has been well tested out of students and will work straight away.' Colin Cooper, Department of computer Science, King's College, University of London
'An exciting new book on randomized algorithms. It nicely covers all the basics, and also has some interesting modern applications for the more advanced student.' Alan Frieze, professor of Mathematics, Carnegie-Mellon University
' … very well written and contains useful material on probability theory and its application in computer science.' Zentralblatt MATH
' … this book offers a very good introduction to randomised algorithms and probabilistic analysis, both for the lecturer and independent reader alike. it is also a good book for those wanting practical examples that can be applied to real world problems.' Mathematics Today
Assuming only an elementary background in discrete mathematics, this 2005 textbook is designed to accompany an introductory course on the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses, including random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales and entropy.See all Product Description