Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12457)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Included in the following conference series:
Conference proceedings info: ECML PKDD 2020.
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About this book
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic.
The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings.
The volumes are organized in topical sections as follows:
Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion.
Part II: deep learning optimization and theory;active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning.
Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics.
Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data.
Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.
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Keywords
- artificial intelligence
- clustering algorithms
- computer vision
- correlation analysis
- data mining
- databases
- education
- evolutionary algorithms
- graph theory
- Human-Computer Interaction (HCI)
- image processing
- machine learning
- network protocols
- neural networks
- pattern recognition
- probability
- signal processing
- user interfaces
Table of contents (43 papers)
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Front Matter
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Privacy and Fairness
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Front Matter
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(Social) Network Analysis and Computational Social Science
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Front Matter
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Other volumes
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Machine Learning and Knowledge Discovery in Databases
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Machine Learning and Knowledge Discovery in Databases
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Machine Learning and Knowledge Discovery in Databases
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Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track
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Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track
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ECML PKDD 2020 Workshops
Editors and Affiliations
Bibliographic Information
Book Title: Machine Learning and Knowledge Discovery in Databases
Book Subtitle: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part I
Editors: Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-67658-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-67657-5Published: 25 February 2021
eBook ISBN: 978-3-030-67658-2Published: 24 February 2021
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: L, 764
Number of Illustrations: 31 b/w illustrations, 188 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Data Structures and Information Theory, Machine Learning, Computer Appl. in Social and Behavioral Sciences, Image Processing and Computer Vision
