Algorithms Illuminated: Omnibus Edition

by Tim Roughgarden

Overview

In Algorithms Illuminated, Tim Roughgarden teaches the basics of algorithms in the most accessible way imaginable. This Omnibus Edition contains the complete text of Parts 1-4, with thorough coverage of asymptotic analysis, graph search and shortest paths, data structures, divide-and-conquer algorithms, greedy algorithms, dynamic programming, and NP-hard problems. Hundreds of worked examples, quizzes, and exercises, plus comprehensive online videos, help readers become better programmers; sharpen their analytical skills; learn to think algorithmically; acquire literacy with computer science's greatest hits; and ace their technical interviews.

Product Details

ISBN-13:	9780999282984
Publisher:	Soundlikeyourself Publishing
Publication date:	09/15/2022
Pages:	690
Product dimensions:	7.20(w) x 10.31(h) x 1.89(d)

About the Author

Tim Roughgarden is a Professor of Computer Science at Columbia University. His research, teaching, and expository writings have been recognized by a Presidential Early Career Award for Scientists and Engineers, the ACM Grace Murray Hopper Award, the EATCS-SIGACT Gödel Prize, a Guggenheim Fellowship, the INFORMS Lancaster Prize, and a Tau Beta Pi Teaching Award. His other books include Twenty Lectures on Algorithmic Game Theory (2016) and Beyond the Worst-Case Analysis of Algorithms (2021).

Table of Contents

Part I. The Basics: 1. Introduction; 2. Asymptotic notation; 3. Divide-and-Conquer algorithms; 4. The master method; 5. QuickSort; 6. Linear-time selection; Part II. Graph Algorithms and Data Structures: 7. Graphs: the Basics; 8. Graph search and its applications; 9. Dijkstra's shortest-path algorithm; 10. The heap data structure; 11. Search trees; 12. Hash tables and Bloom filters; Part III. Greedy Algorithms and Dynamic Programming; 13. Introduction to greedy algorithms; 14. Huffman codes; 15. Minimum spanning trees; 16. Introduction to dynamic programming; 17. Advanced dynamic programming; 18. Shortest paths revisited; Part IV. Algorithms for NP-Hard Problems; 19. What is NP-Hardness?; 20. Compromising on correctness: efficient inexact algorithms; 21. Compromising on speed: exact inefficient algorithms; 22. Proving problems NP-hard; 23. P, NP, and all that; 24. Case study: the FCC incentive auction; Appendix A. Quick review of proofs By induction; Appendix B. Quick review of discrete probability; Epilogue. A field guide to algorithm design; Hints and solutions.

Editorial Reviews

‘Algorithms Illuminated is academic gold for both students and instructors. The most incredible thing about this book is the way it reaches different types of learners. Beginning students love the approach of getting exposed to complex material slowly and methodically, with lots of intuition and illustrations; advanced students can focus their energy on the formal treatment, going back to the intuition as needed. I love this book because it makes very difficult concepts accessible to everyone.' Thomas Cook, US Military Academy at West Point

‘In my experience, students find Algorithms Illuminated much more relatable and motivating to read than other algorithms books. The presentation style is very modern and honest: complicated ideas are broken into digestible chunks with the explicit recognition that the reader is indeed facing deep content; pseudocode, proofs, and mathematical techniques are presented truthfully without hiding "technical/boring" details; and every problem is well-motivated with the actual reasons that computer scientists care about it. The reader gets the feeling that the book is talking directly to them and inviting them to be part of the story, not just a guest who looks at the highlights and moves on.' Saray Shai, Wesleyan College

‘This fabulous book is an ideal introduction to the design and analysis of algorithms. Algorithms Illuminated stands out for its accessible and readable style, with plenty of examples, quizzes and problems for students to check their understanding. The clarity of the exposition brings out the beautiful ideas at the core of the subject. I highly recommend Algorithms Illuminated to anyone starting out with algorithms!' Mary Wootters, Stanford University

‘Tim Roughgarden's Algorithms Illuminated is a well-crafted, thorough, and engaging presentation of algorithms on a wide range of topics. The chapters on NP-hard problems are particularly remarkable, as they overturn the conventional wisdom that this topic is too hard for students to understand. I have found that my students really benefit from this approach and strongly recommend these books to others.' Avraham Leff, Yeshiva College

‘Look through the Table of Contents and you might conclude that this is just another algorithms book. Don't be fooled. What makes this book special – what makes this book the first of its kind – is Tim Roughgarden's singular ability to weave algorithm design with pedagogical design. Learners need opportunities to check their understanding at key points, to study examples, to see algorithms in contexts that they care about, to confront the needed mathematical background buffered by these motivating contexts. It's all here, carried along by Roughgarden's enthusiasm not only for algorithms but also for the people who want to learn them.' Daniel Zingaro, University of Toronto

From the Publisher