Ecml Pkdd 2020 Workshops: Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases - ECML PKDD 2020: SoGood 2020, PDFL 2020, MLCS 2020, NFM

Koprinska, Irena (Editor)/ Kamp, Michael (Editor)/ Appice, Annalisa (Editor)/ Loglisci, Corrado (Editor)/ Antonie, Luiza (Editor)

ISBN 10: 303065964X / ISBN 13: 9783030659646

Verlag: Springer-Nature New York Inc, 2021

Beschreibung

598 pages. 9.25x6.10x1.46 inches. In Stock.

Bestandsnummer des Verkäufers x-303065964X

Bibliografische Details

• Titel: Ecml Pkdd 2020 Workshops: Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases - ECML PKDD 2020: SoGood 2020, PDFL 2020, MLCS 2020, NFM
• Verlag: Springer-Nature New York Inc
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 303065964X
• ISBN-13: 9783030659646
• Einband: Paperback
• Zustand: Brand New
• Gewicht: 0,94 Kilogramm

Über diesen Titel

Inhaltsangabe

This volume constitutes the refereed proceedings of the workshops which complemented the 20th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2020. Due to the COVID-19 pandemic the conference and workshops were held online. 

The 43 papers presented in volume were carefully reviewed and selected from numerous submissions. The volume presents the papers that have been accepted for the following workshops: 5th Workshop on Data Science for Social Good, SoGood 2020; Workshop on Parallel, Distributed and Federated Learning, PDFL 2020; Second Workshop on Machine Learning for Cybersecurity, MLCS 2020, 9th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2020, Workshop on Data Integration and Applications, DINA 2020, Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning, EDML 2020, Second  International Workshop  on  eXplainable  Knowledge  Discovery in  Data Mining, XKDD 2020; 8th International Workshop on News Recommendation and Analytics, INRA 2020. 

The papers from INRA 2020 are published open access and licensed under the terms of the Creative Commons Attribution 4.0 International License.