Investigating the Impact of Pre-trained Word Embeddings on Memorization in Neural Networks
The sensitive information present in the training data, poses a privacy concern for applications as their unintended memorization during training can make models susceptible to membership inference and attribute inference attacks. In this paper, we invest
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Petr Sojka Ivan Kopecˇek Karel Pala Aleš Horák (Eds.)
Text, Speech, and Dialogue 23rd International Conference, TSD 2020 Brno, Czech Republic, September 8–11, 2020 Proceedings
123
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/1244
Petr Sojka Ivan Kopeček Karel Pala Aleš Horák (Eds.) •
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Text, Speech, and Dialogue 23rd International Conference, TSD 2020 Brno, Czech Republic, September 8–11, 2020 Proceedings
123
Editors Petr Sojka Faculty of Informatics Masaryk University Brno, Czech Republic
Ivan Kopeček Faculty of Informatics Masaryk University Brno, Czech Republic
Karel Pala Faculty of Informatics Masaryk University Brno, Czech Republic
Aleš Horák Faculty of Informatics Masaryk University Brno, Czech Republic
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-58322-4 ISBN 978-3-030-58323-1 (eBook) https://doi.org/10.1007/978-3-030-58323-1 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer Nature Switzerland AG 2020 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The annual Text, Speech and Dialogue Conference (TSD), which originated in 1998, is continuing its third decade. During this time, thousands of authors from all over the world have contributed to the proceedings. TSD constitutes a recognized platform for the presentation and
