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  • © 2021

Machine Learning and Principles and Practice of Knowledge Discovery in Databases

International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I

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Conference proceedings info: ECML PKDD 2021.

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Table of contents (62 papers)

  1. eXplainable Knowledge Discovery in Data Mining

    1. This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition

      • Meike Nauta, Annemarie Jutte, Jesper Provoost, Christin Seifert
      Pages 441-456
    2. Explanations for Network Embedding-Based Link Predictions

      • Bo Kang, Jefrey Lijffijt, Tijl De Bie
      Pages 473-488
    3. Exploring Counterfactual Explanations for Classification and Regression Trees

      • Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
      Pages 489-504
    4. Towards Explainable Meta-learning

      • Katarzyna Woźnica, Przemysław Biecek
      Pages 505-520
    5. How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice

      • Tom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki
      Pages 521-533
    6. Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data

      • Zhi Chen, Sarah Tan, Harsha Nori, Kori Inkpen, Yin Lou, Rich Caruana
      Pages 534-551
  2. Bias and Fairness in AI

    1. Front Matter

      Pages 553-557
    2. Algorithmic Factors Influencing Bias in Machine Learning

      • William Blanzeisky, Pádraig Cunningham
      Pages 559-574
    3. Desiderata for Explainable AI in Statistical Production Systems of the European Central Bank

      • Carlos Mougan Navarro, Georgios Kanellos, Thomas Gottron
      Pages 575-590
    4. Robustness of Fairness: An Experimental Analysis

      • Serafina Kamp, Andong Luis Li Zhao, Sindhu Kutty
      Pages 591-606
    5. Co-clustering for Fair Recommendation

      • Gabriel Frisch, Jean-Benoist Leger, Yves Grandvalet
      Pages 607-630
    6. Learning a Fair Distance Function for Situation Testing

      • Daphne Lenders, Toon Calders
      Pages 631-646
    7. Towards Fairness Through Time

      • Alessandro Castelnovo, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Cosentini
      Pages 647-663
  3. International Workshop on Active Inference

    1. Front Matter

      Pages 665-667
    2. Active Inference for Stochastic Control

      • Aswin Paul, Noor Sajid, Manoj Gopalkrishnan, Adeel Razi
      Pages 669-680
    3. Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active Inference

      • Mohamed Baioumy, Corrado Pezzato, Carlos Hernández Corbato, Nick Hawes, Riccardo Ferrari
      Pages 681-691
    4. On the Convergence of DEM’s Linear Parameter Estimator

      • Ajith Anil Meera, Martijn Wisse
      Pages 692-700
    5. Disentangling What and Where for 3D Object-Centric Representations Through Active Inference

      • Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt
      Pages 701-714
    6. Rule Learning Through Active Inductive Inference

      • Tore Erdmann, Christoph Mathys
      Pages 715-725

Other Volumes

  1. Machine Learning and Knowledge Discovery in Databases. Research Track

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

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

    European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part III
  4. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

    European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part IV
  5. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

    European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part V
  6. Machine Learning and Principles and Practice of Knowledge Discovery in Databases

    International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I
  7. Machine Learning and Principles and Practice of Knowledge Discovery in Databases

    International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II

About this book

This two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. 

The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops:
Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021)
Workshop on Parallel, Distributed and Federated Learning (PDFL 2021)
Workshop on Graph Embedding and Mining  (GEM 2021)
Workshop on Machine Learning for Irregular Time-series (ML4ITS 2021)
Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM 2021)
Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2021)
Workshop on Bias and Fairness in AI (BIAS 2021)
Workshop on Workshop on Active Inference (IWAI 2021)
Workshop on Machine Learning for Cybersecurity (MLCS 2021)
Workshop on Machine Learning in Software Engineering (MLiSE 2021)
Workshop on MIning Data for financial applications (MIDAS 2021)
Sixth Workshop on Data Science for Social Good (SoGood 2021)
Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2021)
Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020)
Workshop on Machine Learning for Buildings Energy Management (MLBEM 2021)

Keywords

  • artificial intelligence
  • computer hardware
  • computer networks
  • computer security
  • computer systems
  • computer vision
  • engineering
  • image processing
  • inference
  • inference engines
  • internet
  • machine learning
  • network protocols
  • neural networks
  • probability
  • signal processing
  • software engineering

Editors and Affiliations

  • IKIM, Ruhr-University Bochum, Bochum, Germany

    Michael Kamp

  • University of Sydney, Sydney, Australia

    Irena Koprinska

  • University of Namur, Namur, Belgium

    Adrien Bibal, Benoît Frénay

  • University of Rennes 1, Rennes, France

    Tassadit Bouadi

  • Inria, Rennes, France

    Luis Galárraga

  • University of Antwerp, Antwerp, Belgium

    José Oramas

  • Ruhr University Bochum, Bochum, Germany

    Linara Adilova

  • Royal Holloway University of London, Egham, UK

    Yamuna Krishnamurthy

  • Ghent University, Ghent, Belgium

    Bo Kang, Tim Verbelen

  • Université Jean Monnet, Saint-Etienne cedex 2, France

    Christine Largeron

  • Ghent University, Gent, Belgium

    Jefrey Lijffijt

  • Telecom Paris, Paris, France

    Tiphaine Viard

  • University of Bonn, Bonn, Germany

    Pascal Welke

  • Norwegian Univesity of Science and Technology, Trondheim, Norway

    Massimiliano Ruocco

  • BI Norwegian Business School, Oslo, Norway

    Erlend Aune

  • University of Pisa, Pisa, Italy

    Claudio Gallicchio, Riccardo Guidotti, Anna Monreale

  • University of Duisburg-Essen, Essen, Germany

    Gregor Schiele

  • Graz University of Technology, Graz, Austria

    Franz Pernkopf

  • Xilinx Research, Dublin, Ireland

    Michaela Blott

  • Heidelberg University, Heidelberg, Germany

    Holger Fröning, Günther Schindler

  • ISTI-CNR, Pisa, Italy

    Salvatore Rinzivillo

  • Warsaw University of Technology, Warsaw, Poland

    Przemyslaw Biecek

  • Freie Universität Berlin, Berlin, Germany

    Eirini Ntoutsi

  • Eindhoven University of Technology, Eindhoven, The Netherlands

    Mykola Pechenizkiy

  • Leibniz University Hannover, Hannover, Germany

    Bodo Rosenhahn

  • University of Sussex, Brighton, UK

    Christopher Buckley

  • University of Chieti-Pescara, Chieti, Italy

    Daniela Cialfi

  • Radboud University Nijmegen, Nijmegen, The Netherlands

    Pablo Lanillos

  • McGill University, Montreal, Canada

    Maxwell Ramstead

  • University of Lisbon, Lisboa, Portugal

    Pedro M. Ferreira

  • University of Bari Aldo Moro, Bari, Italy

    Giuseppina Andresini

  • Universita di Bari Aldo Moro, Bari, Italy

    Donato Malerba

  • University of Lisbon, Lisbon, Portugal

    Ibéria Medeiros, Guilherme Graça

  • Shenzhen University, Shenzhen, China

    Philippe Fournier-Viger

  • Harbin Institute of Technology, Harbin, China

    M. Saqib Nawaz

  • University of Córdoba, Córdoba, Spain

    Sebastian Ventura

  • Peking University, Beijing, China

    Meng Sun

  • Noah's Ark Lab, Huawei, Beijing, China

    Min Zhou

  • UniCredit, Milan, Italy

    Valerio Bitetta, Andrea Ferretti

  • UniCredit, Rome, Italy

    Ilaria Bordino

  • Unicredit, Rome, Italy

    Francesco Gullo, Lorenzo Severini

  • ENEA Headquarters, Portici, Italy

    Giovanni Ponti

  • University of Porto, Porto, Portugal

    Rita Ribeiro, João Gama

  • UPC BarcelonaTech, Barcelona, Spain

    Ricard Gavaldà

  • Northwestern University, Chicago, USA

    Lee Cooper

  • PD Personalised Healthcare, Basel, Switzerland

    Naghmeh Ghazaleh

  • University of Lausanne, Lausanne, Switzerland

    Jonas Richiardi

  • ETH Zurich, Basel, Switzerland

    Damian Roqueiro

  • F. Hoffmann–La Roche Ltd, Basel, Switzerland

    Diego Saldana Miranda

  • Novartis Pharma AG, Basel, Switzerland

    Konstantinos Sechidis

Bibliographic Information

  • Book Title: Machine Learning and Principles and Practice of Knowledge Discovery in Databases

  • Book Subtitle: International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I

  • Editors: Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastian Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça

  • Series Title: Communications in Computer and Information Science

  • DOI: https://doi.org/10.1007/978-3-030-93736-2

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-93735-5

  • eBook ISBN: 978-3-030-93736-2

  • Series ISSN: 1865-0929

  • Series E-ISSN: 1865-0937

  • Edition Number: 1

  • Number of Pages: XXV, 882

  • Number of Illustrations: 46 b/w illustrations, 236 illustrations in colour

  • Topics: Artificial Intelligence, Computer Engineering and Networks, Computer Application in Social and Behavioral Sciences, Computers and Education, Mathematics of Computing, Software Engineering

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-93736-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 169.99
Price excludes VAT (USA)