Models of Computation for Big Data

• Main Author: Akerkar, Rajendra (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: SpringerBriefs in Advanced Information and Knowledge Processing,
• Subjects: Algorithms.; Data mining.; Algebras, Linear.; Computers.; Algorithm Analysis and Problem Complexity.; Data Mining and Knowledge Discovery.; Linear Algebra.; Models and Principles.

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...

Table of 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.