Tim Roughgarden

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About Tim Roughgarden

Tim Roughgarden is a Professor of Computer Science at Columbia University. Prior to joining Columbia, he spent 15 years on the computer science faculty at Stanford, following a PhD at Cornell and a postdoc at UC Berkeley. His research interests include the many connections between computer science and economics, as well as the design, analysis, applications, and limitations of algorithms. For his research, he has been awarded the ACM Grace Murray Hopper Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), the Kalai Prize in Computer Science and Game Theory, the Social Choice and Welfare Prize, the Mathematical Programming Society's Tucker Prize, and the EATCS-SIGACT Gödel Prize. He was an invited speaker at the 2006 International Congress of Mathematicians, the Shapley Lecturer at the 2008 World Congress of the Game Theory Society, and a Guggenheim Fellow in 2017. His books include Twenty Lectures on Algorithmic Game Theory (2016) and the Algorithms Illuminated book series (2017-2019).

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Books By Tim Roughgarden

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Algorithms Illuminated (Part 2): Graph Algorithms and Data Structures 4-Aug-2018

by Tim Roughgarden

( 241 )

$9.99 $24.99

Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes solutions to all quizzes and selected problems, and a series of YouTube videos by the author accompanies the book. Part 2 covers graph search and its applications, shortest-path algorithms, and the applications and implementation of several data structures: heaps, search trees, hash tables, and bloom filters. (Part 1 is not a prerequisite.)

Other Formats:: Paperback

Algorithms Illuminated (Part 3): Greedy Algorithms and Dynamic Programming 30-Apr-2019

by Tim Roughgarden

( 218 )

$9.99 $24.99

Accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes hints or solutions to all quizzes and problems, and a series of YouTube videos by the author accompanies the book. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

Other Formats:: Paperback

Algorithms Illuminated: Part 1: The Basics 25-Sep-2017

by Tim Roughgarden

( 384 )

$9.99 $24.99

Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to public-key cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject---a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. The exposition is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details.
Part 1 of the book series covers asymptotic analysis and big-O notation, divide-and-conquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection.

Other Formats:: Paperback

Algorithms Illuminated (Part 4): Algorithms for NP-Hard Problems 15-Jul-2020

by Tim Roughgarden

( 162 )

$9.99 $24.99

Fourth book in a series that provides an accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes hints or solutions to all quizzes and problems, and a series of YouTube videos by the author accompanies the book. Part 4 covers algorithmic tools for tackling NP-hard problems (heuristic algorithms, local search, dynamic programming, MIP and SAT solvers) and techniques for quickly recognizing NP-hard problems in the wild.

Other Formats:: Paperback

Algorithmic Game Theory 24-Sep-2007

by Noam Nisan, Tim Roughgarden, Eva Tardos, Vijay V. Vazirani

( 29 )

$75.95 $79.95

In recent years game theory has had a substantial impact on computer science, especially on Internet- and e-commerce-related issues. Algorithmic Game Theory, first published in 2007, develops the central ideas and results of this exciting area in a clear and succinct manner. More than 40 of the top researchers in this field have written chapters that go from the foundations to the state of the art. Basic chapters on algorithmic methods for equilibria, mechanism design and combinatorial auctions are followed by chapters on important game theory applications such as incentives and pricing, cost sharing, information markets and cryptography and security. This definitive work will set the tone of research for the next few years and beyond. Students, researchers, and practitioners alike need to learn more about these fascinating theoretical developments and their widespread practical application.

Other Formats:: Hardcover

Beyond the Worst-Case Analysis of Algorithms 14-Jan-2021

by Tim Roughgarden

( 10 )

$71.20 $74.95

There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

Other Formats:: Hardcover

Twenty Lectures on Algorithmic Game Theory 30-Aug-2016

by Tim Roughgarden

( 26 )

$45.96 $49.36

Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.

Other Formats:: Hardcover , Paperback

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