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Book Categories |
| Preface | ||
| 1 | Probability | 1 |
| 2 | Some Examples | 49 |
| 3 | Probability Bounds, Approximations, and Computations | 75 |
| 4 | Markov Chains | 103 |
| 5 | The Probabilistic Method | 151 |
| 6 | Martingales | 175 |
| 7 | Poisson Processes | 199 |
| 8 | Queueing Theory | 221 |
| 9 | Simulation | 261 |
| References | 283 | |
| Index | 285 |
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
Justin Hennis
reviewed Probability Models For Computer Science on November 27, 2012
Probability Models For Computer Science
If you read this book as first time in order to understand Computational Complexity, then you're probably not going to like it. You need to read Sipser's textbook before you read this book and make sure that you have a strong background in discrete mathematics (if not, then see Rosen's textbook in Discrete Mathematics). This book is recommended by best people in complexity and algorithms such as Scott Aaronson, Sipser, etc. You need to solve as many exercises as you go.
The book has five parts:
Part I: Algorithms
Part II: Logic
Part III: P and NP
Part IV: Inside P
Part V: Beyond NP
The most important parts are in Part I, III.
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Add Probability Models For Computer Science, 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 stud, Probability Models For Computer Science to the inventory that you are selling on WonderClubX
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Add Probability Models For Computer Science, 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 stud, Probability Models For Computer Science to your collection on WonderClub |
