Models of computation for big data / Rajendra Akerkar.
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...
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Full Text (via Springer) |
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| Main Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2018]
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| Series: | Advanced information and knowledge processing.
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| Subjects: |
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.