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

Lev Rozonoer (u. a.)

ISBN 10: 3319994913 / ISBN 13: 9783319994918

Published by Springer, 2018

About this Item

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 | Lev Rozonoer (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xii | Englisch | 2018 | Springer | EAN 9783319994918 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 114111239

Bibliographic Details

• Title: 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
• Publisher: Springer
• Publication Date: 2018
• Language: English
• ISBN 10: 3319994913
• ISBN 13: 9783319994918
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 20D millimeters 235 millimeters width by 155 millimeters height by 20 millimeters depth
• Weight: 557 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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 essaysby a friend, a student, and a colleague.

About the Author

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.