The Design Of Approximation Algorithms


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Updated: 12.01.2020
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ISBN: 8789611514
Pages in a book: 229
Language: Original
Availability: In stock

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This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms. Design and Analysis of Approximation Algorithms is a graduate course in theoretical computer science taught widely in the universities, both in the United States and abroad. There are, however, very few textbooks available for this course. The Design Of Approximation Algorithms Among those available in the market, most books follow a problem-oriented format; that is, they collected many important combinatorial optimization problems and their approximation algorithms, and organized them based on the types, or applications, of problems, such as geometric-type problems, algebraic-type problems, etc. In the new book proposed here, we follow a more structured, technique-oriented presentation. We organize approximation algorithms into different chapters, based on the design techniques for the algorithms, so that the reader can study approximation algorithms of the same nature together. It helps the reader to better understand the design and analysis techniques for approximation algorithms, and also helps the teacher to present the ideas and techniques of approximation algorithms in a more unified way.

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  2. CSE Approximation Algorithms (Spring )
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It gives a concise treatment of the major techniques, results and references in approximation algorithms and provides an extensive and systematic coverage of this topic up to the frontier of current research. It covers everything from the classics to the latest, most exciting results such as ARV's sparsest cut algorithm, and does so in an extraordinarily clear, rigorous and intuitive manner. The description is lucid, extensive and up-to-date. This book will be very valuable to students and researchers alike. This will become a standard textbook in this area for graduate students and researchers. They do a wonderful job in providing clear and unified explanations of subjects ranging from basic and fundamental algorithmic design techniques to advanced results in the forefront of current research. This book, written by two leading researchers, systematically covers all the important ideas needed to design effective approximation algorithms.

Williamson and David B. WilliamsonDavid B. Shmoys Published DOI: Yet most such problems are NP-hard. View PDF. Save to Library. Create Alert.

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Share This Paper. Figures and Topics from this paper. Citations Publications citing this paper. Blessing of massive scale: spatial graphical model estimation with a total cardinality constraint approach Ethan X. FangHan LiuMengdi Wang.

CSE Approximation Algorithms (Spring )

GutekunstDavid P. References Publications referenced by this paper. Introduction to Algorithms Thomas H. CormenCharles E. LeisersonRonald L. On the power of unique 2-prover 1-round games Subhash Khot. GoemansDavid P.

  • The Design Of Approximation Algorithms, This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms.
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  • The Euclidean Traveling Salesman Problem -- Convergence Trust region Wolfe conditions.
  • Be the first. Interesting discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design, to computer science problems in databases, to advertising issues in viral marketing.

Offline and online facility leasing Chandrashekhar NagarajanDavid P. Approximating the smallest k-edge connected spanning subgraph by LP-rounding Harold N. GabowMichel X.

[PDF] The Design of Approximation Algorithms Semantic Scholar

The primal-dual method for approximation algorithms David P. ChudakTim RoughgardenDavid P. Related Papers. By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy PolicyTerms of Serviceand Dataset License.


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ghostbusters Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing. Yet most such problems are NP-hard. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions.
trafikom In computer science and operations research , approximation algorithms are efficient algorithms that find approximate solutions to NP-hard optimization problems with provable guarantees on the distance of the returned solution to the optimal one. Under this conjecture, a wide class of optimization problems cannot be solved exactly in polynomial time.