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Models of computation for big data

Author: Rajendra Akerkar
Publisher: Cham, Switzerland : Springer, [2018]
Series: Advanced information and knowledge processing.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Rajendra Akerkar
ISBN: 9783319918518 3319918516
OCLC Number: 1080604941
Description: 1 online resource
Contents: Preface --
Streaming Models --
Introduction --
Indyk's Algorithm --
Point Query --
Sketching --
Sub-Linear Time Models --
Introduction --
Dimentionality Reduction --
Johnson Lindenstrauss Lower Bound --
Fast Johnson Lindenstrauss Transform --
Sublinear Time Algorithmic Models --
Linear Algebraic Models --
Introduction --
Subspace Embeddings --
Low-Rank Approximation --
The Matrix Completion Problem --
Other Computational Models --
References.
Series Title: Advanced information and knowledge processing.
Responsibility: Rajendra Akerkar.

Abstract:

In many recent application situations, however, the size of the input data is too large to fit within memory.Models of Computation for Big Data, covers mathematical models for developing such  Read more...

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