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Book Categories |
| Preface | ||
| 1 | Combinatorics and Probability | 1 |
| 2 | Discrete Distributions | 91 |
| 3 | Simulation | 179 |
| 4 | Discrete Decision Theory | 271 |
| 5 | Real Line-Probability | 371 |
| 6 | Continuous Distributions | 437 |
| 7 | Parameter Estimation | 545 |
| A | Analytical Tools | 641 |
| B | Statistical Tables | 713 |
| Bibliography | 733 | |
| Index | 739 |
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
Jeff Caudron
reviewed Probability and Statistics for Computer Science on April 01, 2016
Probability and Statistics 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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