Measures of Complexity Festschrift for Alexey Chervonenkis
This book brings together historical notes, reviews of research developments, fresh ideas on how to make VC (Vapnik–Chervonenkis) guarantees tighter, and new technical contributions in the areas of machine learning, statistical inference, classification,
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sures of Complexity Festschrift for Alexey Chervonenkis
Measures of Complexity
Vladimir Vovk Harris Papadopoulos Alexander Gammerman •
Editors
Measures of Complexity Festschrift for Alexey Chervonenkis
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Editors Vladimir Vovk Department of Computer Science Royal Holloway, University of London Egham, Surrey UK
Alexander Gammerman Department of Computer Science Royal Holloway, University of London Egham, Surrey UK
Harris Papadopoulos Department of Computer Science and Engineering Frederick University Nicosia Cyprus
ISBN 978-3-319-21851-9 DOI 10.1007/978-3-319-21852-6
ISBN 978-3-319-21852-6
(eBook)
Library of Congress Control Number: 2015946591 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
Alexey Chervonenkis (1938–2014)
Preface
In our media-centered age obsessed with various semi-known and unknown personalities and celebrities, the life and work of one of the founders of modern machine learning, Alexey Chervonenkis, somehow remains largely unknown. Alexey celebrated his 75th anniversary in 2013, and several of his colleagues organized a symposium devoted to his life and work. The symposium was held in Paphos, Cyprus, on October 2, 2013, and was called “Measures of Complexity.” To some degree, the present volume is an outcome of that meeting; some of the chapters (such as Chap. 13 by Alexey Chervonenkis and Chaps. 4 and 14 by Richard Dudley) are based on the talks delivered by their authors at the symposium. But the vast majority of the chapters were prepared specifically for this volume. Two years earlier the machine learning community had celebrated the 75th anniversary of Alexey’s close friend and co-author Vladimir Vapnik, and the Vapnik Festschrift was published recently as [1]. Compared to the Vapnik Festschrift, thi
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