Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: thebookforest.com, San Rafael, CA, U.S.A.
Condition: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Condition: New.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: California Books, Miami, FL, U.S.A.
Condition: New.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Language: English
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. 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. Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Ria Christie Collections, Uxbridge, United Kingdom
US$ 86.63
Quantity: Over 20 available
Add to basketCondition: New. In.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
US$ 86.61
Quantity: Over 20 available
Add to basketCondition: New.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
US$ 97.52
Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
Language: English
Published by Cambridge University Press CUP, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Revaluation Books, Exeter, United Kingdom
US$ 130.75
Quantity: 2 available
Add to basketHardcover. Condition: Brand New. 686 pages. 10.00x7.00x1.55 inches. In Stock.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Mispah books, Redhill, SURRE, United Kingdom
US$ 151.54
Quantity: 1 available
Add to basketHardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Revaluation Books, Exeter, United Kingdom
US$ 91.85
Quantity: 1 available
Add to basketHardcover. Condition: Brand New. 686 pages. 10.00x7.00x1.55 inches. In Stock. This item is printed on demand.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Majestic Books, Hounslow, United Kingdom
US$ 130.19
Quantity: 4 available
Add to basketCondition: New. Print on Demand.
Language: English
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: CitiRetail, Stevenage, United Kingdom
US$ 96.60
Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. 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. Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case anal.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND.
Language: English
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. 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. Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108494315 ISBN 13: 9781108494311
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Beyond the Worst-Case Analysis of Algorithms | Tim Roughgarden | Buch | Gebunden | Englisch | 2021 | Cambridge University Press | EAN 9781108494311 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.