Pearls Algorithm Engineering by Paolo Ferragina (13 results)
- Hardcover
Seller: SN Books Ltd, Thetford, United KingdomSN Books Ltd
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hardcover. Condition: Fine. Orders shipped daily from the UK. Professional seller.
- Hardcover
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- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 326 pages. 9.61x6.69x0.75 inches. In Stock.
- Hardcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Hardcover
- Print on Demand
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
- Hardcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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- Hardcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorPaolo Ferragina is Professor of Algorithms at the University of Pisa, with a post-doc at the Max-Planck Institute for Informatics. He served his university as Vice Rector for ICT (2019-22) and for Applied Research and .…
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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£ 72.99
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Hardcover. Condition: new. Hardcover. There are many textbooks on algorithms focusing on big-O notation and basic design principles. This book offers a unique approach to taking the design and analyses to the level of predictable practical efficiency, discussing core and classic algorithmic problems that arise in the development of big data applications, and presenting elegant solutions of increasing sophistication and efficiency. Solutions are analyzed within the classic RAM model, and the more practically significant external-memory model that allows one to perform I/O-complexity evaluations. Chapters cover various data types, including integers, strings, trees, and graphs, algorithmic tools such as sampling, sorting, data compression, and searching in dictionaries and texts, and lastly, recent developments regarding compressed data structures. Algorithmic solutions are accompanied by detailed pseudocode and many running examples, thus enriching the toolboxes of students, researchers, and professionals interested in effective and efficient processing of big data. This book provides students, researchers and professionals working in big data applications with solutions to core algorithmic problems, analyzed within RAM and external-memory models of computation. Pseudocode and running examples deal with various data types, and algorithmic tools for sampling, sorting, search, and data compression are included. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
