Probabiliy models for computer science Ross, Sheldon M.

By:

Ross, Sheldon M

Material type: Text

TextPublication details: United States Academic Press 2002 Description: xii, 288 pISBN:

9788131203071

Subject(s):

DDC classification:

519.1

Summary: 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. The key feature of this book is its many interesting examples and exercises that have been chosen to illuminate the techniques presented. For instance, there are examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organizing list problems, antichains, minimal and maximal cuts in graphs, random permutations, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queing networks, distributed workload models, and more.

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad	519.1 R6P7 (Browse shelf(Opens below))	Available		159110

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Previous	519.1 R6F4/2003-4 A first course in probability	519.1 R6F41 First look at rigorous probability theory	519.1 R6I6/2001 Introduction to probability models	519.1 R6P7 Probabiliy models for computer science	519.1 R6S8 Stochastic processes	519.1 R9L4 Litigation and settlement in a game with incomplete information: an experimental study	519.1 S3D9 Dynamic and stochastic efficiency analysis: economics of data envelopment analysis	Next

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. The key feature of this book is its many interesting examples and exercises that have been chosen to illuminate the techniques presented. For instance, there are examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organizing list problems, antichains, minimal and maximal cuts in graphs, random permutations, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queing networks, distributed workload models, and more.

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