Meta-Algorithmics
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Meta-Algorithmics: Patterns for Robust, Low Cost, High Quality Systems(IEEE Press)

Meta-Algorithmics: Patterns for Robust, Low Cost, High Quality Systems(IEEE Press)


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About the Book

Table of Contents:
1 Introduction and Overview 1 1.1 Introduction 1 1.2 Why Is This Book Important? 2 1.3 Organization of the Book 3 1.4 Informatics 4 1.5 Ensemble Learning 6 1.6 Machine Learning/Intelligence 7 1.7 Artificial Intelligence 22 1.8 Data Mining/Knowledge Discovery 31 1.9 Classification 32 1.10 Recognition 38 1.11 System-Based Analysis 39 1.12 Summary 39 References 40 2 Parallel Forms of Parallelism 42 2.1 Introduction 42 2.2 Parallelism by Task 43 2.3 Parallelism by Component 52 2.4 Parallelism by Meta-algorithm 64 2.5 Summary 71 References 72 3 Domain Areas: Where Is This Relevant? 73 3.1 Introduction 73 3.2 Overview of the Domains 74 3.3 Primary Domains 75 3.4 Secondary Domains 86 3.5 Summary 101 References 102 4 Applications of Parallelism by Task 104 4.1 Introduction 104 4.2 Primary Domains 105 4.3 Summary 135 References 136 5 Application of Parallelism by Component 137 5.1 Introduction 137 5.2 Primary Domains 138 5.3 Summary 172 References 173 6 Introduction to Meta-algorithmics 175 6.1 Introduction 175 6.2 First-Order Meta-algorithmics 178 6.3 Second-Order Meta-algorithmics 195 6.4 Third-Order Meta-algorithmics 218 6.5 Summary 240 References 240 7 First-Order Meta-algorithmics and Their Applications 241 7.1 Introduction 241 7.2 First-Order Meta-algorithmics and the “Black Box” 241 7.3 Primary Domains 242 7.4 Secondary Domains 257 7.5 Summary 271 References 271 8 Second-Order Meta-algorithmics and Their Applications 272 8.1 Introduction 272 8.2 Second-Order Meta-algorithmics and Targeting the “Fringes” 273 8.3 Primary Domains 279 8.4 Secondary Domains 304 8.5 Summary 308 References 308 9 Third-Order Meta-algorithmics and Their Applications 310 9.1 Introduction 310 9.2 Third-Order Meta-algorithmic Patterns 311 9.3 Primary Domains 313 9.4 Secondary Domains 328 9.5 Summary 340 References 341 10 Building More Robust Systems 342 10.1 Introduction 342 10.2 Summarization 342 10.3 Cloud Systems 350 10.4 Mobile Systems 353 10.5 Scheduling 355 10.6 Classification 356 10.7 Summary 358 Reference 359 11 The Future 360 11.1 Recapitulation 360 11.2 The Pattern of all Patience 362 11.3 Beyond the Pale 365 11.4 Coming Soon 367 11.5 Summary 368 References 368 Index

About the Author :
Steven J. Simske, Hewlett-Packard Labs, Colorado, USA Dr Simske is currently Director of the Document Ecosystem Lab, at Hewlett-Packard Labs, Colorado, USA. He has been working in algorithms, imaging, machine learning and classification for the past 20 years. As an engineer at HP Labs, he has designed, developed and shipped products associated with a very broad array of domains—document understanding, image segmentation and understanding, speech recognition, medical signal processing and imaging, biometrics, natural language processing, surveillance, optical character recognition, security analytics and security printing. The advantages of systematic meta-algorithmic approaches to the robustness, accuracy, cost and/or other system features which is the focus of the book has been evident across these domains. Dr. Simske is an HP Fellow, IS&T Fellow and IEEE Senior Member. He has published 300 articles and book chapters; and holds 45 US Patents primarily in the areas of classification, machine learning, and large system design and development.


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Product Details
  • ISBN-13: 9781118626696
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: Wiley-IEEE Press
  • Language: English
  • Series Title: IEEE Press
  • ISBN-10: 1118626699
  • Publisher Date: 30 May 2013
  • Binding: Digital (delivered electronically)
  • No of Pages: 392
  • Sub Title: Patterns for Robust, Low Cost, High Quality Systems


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