Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Back to School Savings: Save up to 30% on print books and eBooks. No promo code needed.
Back to School Savings: Save up to 30%
Probability Models for Computer Science
1st Edition - June 8, 2001
Author: Sheldon M. Ross
Hardback ISBN:
9 7 8 - 0 - 1 2 - 5 9 8 0 5 1 - 7
Other ISBN:
9 7 8 - 0 - 0 8 - 0 5 1 4 8 8 - 8
The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely… Read more
Purchase Options
The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners.
Many interesting examples and exercises have been chosen to illuminate the techniques presented
Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented
Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented
Review of Probability * Some Examples * Poisson and Compound Poisson Variables, Approximations and Processes * Markov Chains * Queuing * Random Algorithms and the Probabilistic Method * Martingales * Simulation *
- No. of pages: 304
- Language: English
- Published: June 8, 2001
- Imprint: Academic Press
- Hardback ISBN: 9780125980517
- Other ISBN: 9780080514888
SR
Sheldon M. Ross
Dr. Sheldon M. Ross is a professor in the Department of Industrial and Systems Engineering at the University of Southern California. He received his PhD in statistics at Stanford University in 1968. He has published many technical articles and textbooks in the areas of statistics and applied probability. Among his texts are A First Course in Probability, Introduction to Probability Models, Stochastic Processes, and Introductory Statistics. Professor Ross is the founding and continuing editor of the journal Probability in the Engineering and Informational Sciences. He is a Fellow of the Institute of Mathematical Statistics, a Fellow of INFORMS, and a recipient of the Humboldt US Senior Scientist Award.
Affiliations and expertise
Professor, Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, USA