Isbn: 9780817633288 - lecture notes on bucket algorithms: 6 (16 risultati)

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  • Lingua: Inglese

    Editore: Secaucus, New Jersey, U.S.A.: Birkhauser, 1986

    0817633286 / 9780817633288

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  • Lingua: Inglese

    Editore: Birkhäuser, 1986

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  • Lingua: Inglese

    Editore: Birkhäuser, 1986

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  • Lingua: Inglese

    Editore: Birkhäuser, 1986

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  • Lingua: Inglese

    Editore: Birkhauser 1985-01, 1985

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  • Lingua: Inglese

    Editore: Birkhauser Boston Inc, 1985

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    Condizione: New. Series: Progress in Computer Science and Applied Logic. Num Pages: 155 pages, biography. BIC Classification: YQS. Category: (P) Professional & Vocational. Dimension: 229 x 152 x 9. Weight in Grams: 380. . 1985. Softcover reprint of the original 1st ed. 1986. Paperback. . . . .

  • Lingua: Inglese

    Editore: Springer, 1986

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  • Lingua: Inglese

    Editore: Birkhauser, 1986

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

  • Lingua: Inglese

    Editore: Birkhauser Boston Inc, 1986

    0817633286 / 9780817633288

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    Condizione: New. Series: Progress in Computer Science and Applied Logic. Num Pages: 155 pages, biography. BIC Classification: YQS. Category: (P) Professional & Vocational. Dimension: 229 x 152 x 9. Weight in Grams: 380. . 1985. Softcover reprint of the original 1st ed. 1986. Paperback. . . . . Books ship from the US and Ireland.

  • Lingua: Inglese

    Editore: Birkhäuser, Birkhäuser, 1986

    0817633286 / 9780817633288

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    Taschenbuch. Condizione: 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.

  • Lingua: Inglese

    Editore: Birkhäuser Boston, 1985

    0817633286 / 9780817633288

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    Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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.

  • Lingua: Inglese

    Editore: Springer, 1986

    0817633286 / 9780817633288

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

  • Lingua: Inglese

    Editore: Springer, 1986

    0817633286 / 9780817633288

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    Condizione: New. PRINT ON DEMAND pp. 160.

  • Lingua: Inglese

    Editore: Birkhäuser Boston, 1985

    0817633286 / 9780817633288

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    Condizione: 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.

  • Lingua: Inglese

    Editore: Birkhäuser Boston Jan 1985, 1985

    0817633286 / 9780817633288

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: 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.

  • Lingua: Inglese

    Editore: Birkhäuser, Birkhäuser Jan 1985, 1985

    0817633286 / 9780817633288

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    Taschenbuch. Condizione: 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 Nature c/o IBS, Benzstrasse 21, 48619 Heek 160 pp. Englisch.