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Nuria Oliver - Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III

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Nuria Oliver Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III

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The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021. The conference was originally planned to take place in Bilbao, Spain, but changed to an online event due to the COVID-19 pandemic.

The 210 full papers presented in these proceedings were carefully reviewed and selected from a total of 869 submissions.

The volumes are organized in topical sections as follows:

Research Track:

Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised and few-shot learning; learning algorithms and applications.

Part II: Generative models; algorithms and learning theory; graphs and networks; interpretation, explainability, transparency, safety.

Part III: Generative models; search and optimization; supervised learning; text mining and natural language processing; image processing, computer vision and visual analytics.

Applied Data Science Track:

Part IV: Anomaly detection and malware; spatio-temporal data; e-commerce and finance; healthcare and medical applications (including Covid); mobility and transportation.

Part V: Automating machine learning, optimization, and feature engineering; machine learning based simulations and knowledge discovery; recommender systems and behavior modeling; natural language processing; remote sensing, image and video processing; social media.

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Nuria Oliver - Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III
Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III
Nuria Oliver
Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III

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Book cover of Machine Learning and Knowledge Discovery in Databases Research - photo 1
Book cover of Machine Learning and Knowledge Discovery in Databases. Research Track
Volume 12977
Lecture Notes in Computer Science Lecture Notes in Artificial Intelligence
Series Editors
Randy Goebel
University of Alberta, Edmonton, Canada
Yuzuru Tanaka
Hokkaido University, Sapporo, Japan
Wolfgang Wahlster
DFKI and Saarland University, Saarbrcken, Germany
Founding Editor
Jrg Siekmann
DFKI and Saarland University, Saarbrcken, Germany

More information about this subseries at http://www.springer.com/series/1244

Editors
Nuria Oliver , Fernando Prez-Cruz , Stefan Kramer , Jesse Read and Jose A. Lozano
Machine Learning and Knowledge Discovery in Databases. Research Track
European Conference, ECML PKDD 2021, Bilbao, Spain, September 1317, 2021, Proceedings, Part III
1st ed. 2021
Logo of the publisher Editors Nuria Oliver ELLIS - The European - photo 2
Logo of the publisher
Editors
Nuria Oliver
ELLIS - The European Laboratory for Learning and Intelligent Systems, Alicante, Spain
Vodafone Institute for Society and Communications, Berlin, Germany
Data-Pop Alliance, New York, USA
Avda Universidad,San Vicente del Raspeig, Alicante, Spain
Fernando Prez-Cruz
ETHZ and EPFL, Zrich, Switzerland
Stefan Kramer
Johannes Gutenberg University of Mainz, Mainz, Germany
Jesse Read
cole Polytechnique, Palaiseau, France
Jose A. Lozano
Basque Center for Applied Mathematics, Bilbao, Spain
ISSN 0302-9743 e-ISSN 1611-3349
Lecture Notes in Computer Science Lecture Notes in Artificial Intelligence
ISBN 978-3-030-86522-1 e-ISBN 978-3-030-86523-8
https://doi.org/10.1007/978-3-030-86523-8
Springer Nature Switzerland AG 2021
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

This edition of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021) has still been affected by the COVID-19 pandemic. Unfortunately it had to be held online and we could only meet each other virtually. However, the experience gained in the previous edition joined to the knowledge collected from other virtual conferences allowed us to provide an attractive and engaging agenda.

ECML PKDD is an annual conference that provides an international forum for the latest research in all areas related to machine learning and knowledge discovery in databases, including innovative applications. It is the leading European machine learning and data mining conference and builds upon a very successful series of ECML PKDD conferences. Scheduled to take place in Bilbao, Spain, ECML PKDD 2021 was held fully virtually, during September 1317, 2021. The conference attracted over 1000 participants from all over the world. More generally, the conference received substantial attention from industry through sponsorship, participation, and also the industry track.

The main conference program consisted of presentations of 210 accepted conference papers, 40 papers accepted in the journal track and 4 keynote talks: Jie Tang (Tsinghua University), Susan Athey (Stanford University), Joaquin Quionero Candela (Facebook), and Marta Kwiatkowska (University of Oxford). In addition, there were 22 workshops, 8 tutorials, 2 combined workshop-tutorials, the PhD forum, and the discovery challenge. Papers presented during the three main conference days were organized in three different tracks:

  • Research Track: research or methodology papers from all areas in machine learning, knowledge discovery, and data mining.

  • Applied Data Science Track: papers on novel applications of machine learning, data mining, and knowledge discovery to solve real-world use cases, thereby bridging the gap between practice and current theory.

  • Journal Track: papers that were published in special issues of the Springer journals Machine Learning and Data Mining and Knowledge Discovery.

We received a similar number of submissions to last year with 685 and 220 submissions for the Research and Applied Data Science Tracks respectively. We accepted 146 (21%) and 64 (29%) of these. In addition, there were 40 papers from the Journal Track. All in all, the high-quality submissions allowed us to put together an exceptionally rich and exciting program.

The Awards Committee selected research papers that were considered to be of exceptional quality and worthy of special recognition:

  • Best (Student) Machine Learning Paper Award: Reparameterized Sampling for Generative Adversarial Networks, by Yifei Wang, Yisen Wang, Jiansheng Yang and Zhouchen Lin.

  • First Runner-up (Student) Machine Learning Paper Award: Continual Learning with Dual Regularizations, by Xuejun Han and Yuhong Guo.

  • Best Applied Data Science Paper Award: Open Data Science to fight COVID-19: Winning the 500k XPRIZE Pandemic Response Challenge, by Miguel Angel Lozano, Oscar Garibo, Eloy Piol, Miguel Rebollo, Kristina Polotskaya, Miguel Angel Garcia-March, J. Alberto Conejero, Francisco Escolano and Nuria Oliver.

  • Best Student Data Mining Paper Award: Conditional Neural Relational Inference for Interacting Systems, by Joao Candido Ramos, Lionel Blond, Stphane Armand and Alexandros Kalousis.

  • Test of Time Award for highest-impact paper from ECML PKDD 2011: Influence and Passivity in Social Media, by Daniel M. Romero, Wojciech Galuba, Sitaram Asur and Bernardo A. Huberman.

We would like to wholeheartedly thank all participants, authors, Program Committee members, area chairs, session chairs, volunteers, co-organizers, and organizers of workshops and tutorials for their contributions that helped make ECML PKDD 2021 a great success. We would also like to thank the ECML PKDD Steering Committee and all sponsors.

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