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Braverman Readings in Machine Learning. Key Ideas from Inception to Current State

International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks

Editors: Rozonoer, Lev, Mirkin, Boris, Muchnik, Ilya (Eds.)

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  • Oriented at students, developers and practitioners in machine learning and data analysis
  • Provides useful insights into the role of parameters
  • Interesting to historians
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eBook $59.99
price for USA in USD (gross)
  • ISBN 978-3-319-99492-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $79.99
price for USA in USD
  • ISBN 978-3-319-99491-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This state-of-the-art survey is dedicated to the memory of Emmanuil Markovich Braverman (1931-1977), a pioneer in developing machine learning theory.
The 12 revised full papers and 4 short papers included in this volume were presented at the conference "Braverman Readings in Machine Learning: Key Ideas from Inception to Current State" held in Boston, MA, USA, in April 2017, commemorating the 40th anniversary of Emmanuil Braverman's decease. The papers present an overview of some of Braverman's ideas and approaches.
The collection is divided in three parts. The first part bridges the past and the present and covers the concept of kernel function and its application to signal and image analysis as well as clustering. The second part presents a set of extensions of Braverman's work to issues of current interest both in theory and applications of machine learning. The third part includes short essays by a friend, a student, and a colleague.

About the authors

Lev Rozonoer, West Newton, MA, USA;Boris Mirkin, National Research University Higher School of Economics, Moscow, Russian Federation;Ilya Muchnik, Rutgers University, Piscataway, NJ, USA.

Table of contents (18 chapters)

Table of contents (18 chapters)
  • Potential Functions for Signals and Symbolic Sequences

    Pages 3-31

    Sulimova, Valentina (et al.)

  • Braverman’s Spectrum and Matrix Diagonalization Versus iK-Means: A Unified Framework for Clustering

    Pages 32-51

    Mirkin, Boris

  • Compactness Hypothesis, Potential Functions, and Rectifying Linear Space in Machine Learning

    Pages 52-102

    Mottl, Vadim (et al.)

  • Conformal Predictive Distributions with Kernels

    Pages 103-121

    Vovk, Vladimir (et al.)

  • On the Concept of Compositional Complexity

    Pages 122-127

    Rozonoer, Lev I.

Buy this book

eBook $59.99
price for USA in USD (gross)
  • ISBN 978-3-319-99492-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $79.99
price for USA in USD
  • ISBN 978-3-319-99491-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Braverman Readings in Machine Learning. Key Ideas from Inception to Current State
Book Subtitle
International Conference Commemorating the 40th Anniversary of Emmanuil Braverman's Decease, Boston, MA, USA, April 28-30, 2017, Invited Talks
Editors
  • Lev Rozonoer
  • Boris Mirkin
  • Ilya Muchnik
Series Title
Lecture Notes in Artificial Intelligence
Series Volume
11100
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-319-99492-5
DOI
10.1007/978-3-319-99492-5
Softcover ISBN
978-3-319-99491-8
Edition Number
1
Number of Pages
XII, 353
Number of Illustrations
65 b/w illustrations
Topics