Cantitate/Preț
Produs

Models of Computation for Big Data: Advanced Information and Knowledge Processing

Autor Rajendra Akerkar
en Limba Engleză Paperback – 17 dec 2018
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 is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. 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 algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.

Citește tot Restrânge

Din seria Advanced Information and Knowledge Processing

Preț: 35967 lei

Preț vechi: 44959 lei
-20%

Puncte Express: 540

Preț estimativ în valută:
6891 7464$ 5909£

Carte tipărită la comandă

Livrare economică 06-11 mai

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319918501
ISBN-10: 3319918508
Pagini: 100
Ilustrații: VIII, 104 p. 3 illus.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.17 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Advanced Information and Knowledge Processing, SpringerBriefs in Advanced Information and Knowledge Processing

Locul publicării:Cham, Switzerland

Cuprins

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

Caracteristici

Focuses on the fundamental principles of algorithm design for big data processing
Covers advanced models of computation relevant for developing memory-efficient algorithms
Advanced-level students and researchers focusing on computer and data science will find this book valuable as a text or reference book