lecture notes bucket algorithms (25 resultados)

Softcover. Condición: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 1985. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Edition 1985. Ammareal gives back up to 15% of this item's net price to charity organizations.

Condición: Sehr gut. Zustand: Sehr gut | Seiten: 160 | Sprache: Englisch | Produktart: Bücher.

Condición: Good. Birkhauser, 1986. Cover rubbed/bumped, lightly soiled, corners/edges/spine ends lightly rubbed/bumped, spine quite sunned; very light pencil erasures at ffep; binding tight; edges and interior intact and clean, except where noted. hardcover. Good.

Condición: Good. Birkhauser, 1986. Cover very lightly rubbed/bumped; edges lightly soiled; pastedowns/endpapers faintly soiled; binding tight; cover and interior intact and clean, except where noted. hardcover. Good.

gebundene Ausgabe. Condición: Gut. 146 Seiten; graph. Darst. ; Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 400.

Hardcover. Condición: Near Fine. hardback book in near fine conition.

Condición: New. In.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Hashing algorithms scramble data and create pseudo-uniform data distribu tions. Bucket algorithms operate on raw untransformed data which are parti tioned Into groups according to membership In equl-slzed d-dlmenslonal hyperrec tangles, called cells or buckets. The bucket data structure Is rather sensitive to the distribution of the data. In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the dis tribution of the data. The results are Illustrated on standard searching, sorting and selection problems, as well as on a variety of problems In computational geometry and operations research. The notes grew partially from a graduate course on probability theory In computer science. I wish to thank Elizabeth Van Gulick for her help with the manuscript, and David Avis, Hanna AYukawa, Vasek Chvatal, Beatrice Devroye, Hossam EI Glndy, Duncan McCallum, Magda McCallum, Godfrled Toussaint and Sue Whltesldes'for making the School of Computer Science at McGill University such an enjoyable place. The work was supported by NSERC Grant A3456 and by FCAC Grant EQ-1679. INTRODUCTION 1 INTRODUCTION It Is not a secret that methods based upon the truncation of data have good expected time performance. For example, for nice distributions of the data, searching Is often better done via a hashing data structure Instead of via a search tree. The speed one observes In practice Is due to the fact that the truncation operation Is a constant time operation.

Condición: New. pp. 160.

Condición: New. pp. 160 23:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on White w/Gloss Lam.

Hardcover. Condición: Brand New. 155 pages. 8.90x5.90x0.50 inches. In Stock.

Condición: New. pp. 160.

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Paperback. Condición: Very Good. Very Good. book.

Paperback. Condición: Very Good. Ex-Library hardcover in very nice condition with all the usual markings and attachments. Text block clean and unmarked. Tight binding.

Hardcover. Condición: Used: Good. former library 1986 hc no dj withdrawn stamp in book/ on edge of pages clean text No. 6 146 pages/// L-13.

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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Hashing algorithms scramble data and create pseudo-uniform data distribu tions. Bucket algorithms operate on raw untransformed data which are parti tioned Into groups according to membership In equl-slzed d-dlmenslonal hyperrec tangles, called cells or buck.

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 380.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Hashing algorithms scramble data and create pseudo-uniform data distribu tions. Bucket algorithms operate on raw untransformed data which are parti tioned Into groups according to membership In equl-slzed d-dlmenslonal hyperrec tangles, called cells or buckets. The bucket data structure Is rather sensitive to the distribution of the data. In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the dis tribution of the data. The results are Illustrated on standard searching, sorting and selection problems, as well as on a variety of problems In computational geometry and operations research. The notes grew partially from a graduate course on probability theory In computer science. I wish to thank Elizabeth Van Gulick for her help with the manuscript, and David Avis, Hanna AYukawa, Vasek Chvatal, Beatrice Devroye, Hossam EI Glndy, Duncan McCallum, Magda McCallum, Godfrled Toussaint and Sue Whltesldes'for making the School of Computer Science at McGill University such an enjoyable place. The work was supported by NSERC Grant A3456 and by FCAC Grant EQ-1679. INTRODUCTION 1 INTRODUCTION It Is not a secret that methods based upon the truncation of data have good expected time performance. For example, for nice distributions of the data, searching Is often better done via a hashing data structure Instead of via a search tree. The speed one observes In practice Is due to the fact that the truncation operation Is a constant time operation.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 160 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Hashing algorithms scramble data and create pseudo-uniform data distribu tions. Bucket algorithms operate on raw untransformed data which are parti tioned Into groups according to membership In equl-slzed d-dlmenslonal hyperrec tangles, called cells or buckets. The bucket data structure Is rather sensitive to the distribution of the data. In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the dis tribution of the data. The results are Illustrated on standard searching, sorting and selection problems, as well as on a variety of problems In computational geometry and operations research. The notes grew partially from a graduate course on probability theory In computer science. I wish to thank Elizabeth Van Gulick for her help with the manuscript, and David Avis, Hanna AYukawa, Vasek Chvatal, Beatrice Devroye, Hossam EI Glndy, Duncan McCallum, Magda McCallum, Godfrled Toussaint and Sue Whltesldes'for making the School of Computer Science at McGill University such an enjoyable place. The work was supported by NSERC Grant A3456 and by FCAC Grant EQ-1679. INTRODUCTION 1 INTRODUCTION It Is not a secret that methods based upon the truncation of data have good expected time performance. For example, for nice distributions of the data, searching Is often better done via a hashing data structure Instead of via a search tree. The speed one observes In practice Is due to the fact that the truncation operation Is a constant time operation. 160 pp. Englisch.