EUR 136,16
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 165,29
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 165,29
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Publicado por Springer US, Springer New York, 2011
ISBN 10: 1461332842 ISBN 13: 9781461332848
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 164,49
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The technique of randomization has been employed to solve numerous prob lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs.
EUR 165,28
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 179,40
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 182,13
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
EUR 180,59
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 178,14
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoGebunden. Condición: New.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 193,53
Convertir monedaCantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 157,68
Convertir monedaCantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 232,99
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. reprint edition. 352 pages. 9.45x6.30x0.72 inches. In Stock.
EUR 247,94
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. Neuware - The technique of randomization has been employed to solve numerous prob lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
Convertir monedaCantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The technique of randomization has been employed to solve numerous prob lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs. 316 pp. Englisch.
Publicado por Springer US, Springer New York Okt 2011, 2011
ISBN 10: 1461332842 ISBN 13: 9781461332848
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The technique of randomization has been employed to solve numerous prob lems of computing both sequentially and in parallel. Examples of randomized algorithms that are asymptotically better than their deterministic counterparts in solving various fundamental problems abound. Randomized algorithms have the advantages of simplicity and better performance both in theory and often in practice. This book is a collection of articles written by renowned experts in the area of randomized parallel computing. A brief introduction to randomized algorithms In the aflalysis of algorithms, at least three different measures of performance can be used: the best case, the worst case, and the average case. Often, the average case run time of an algorithm is much smaller than the worst case. 2 For instance, the worst case run time of Hoare's quicksort is O(n ), whereas its average case run time is only O( n log n). The average case analysis is conducted with an assumption on the input space. The assumption made to arrive at the O( n log n) average run time for quicksort is that each input permutation is equally likely. Clearly, any average case analysis is only as good as how valid the assumption made on the input space is. Randomized algorithms achieve superior performances without making any assumptions on the inputs by making coin flips within the algorithm. Any analysis done of randomized algorithms will be valid for all p0:.sible inputs.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 316 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 200,82
Convertir monedaCantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 205,56
Convertir monedaCantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.