Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12461)
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 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
- bayesian networks
- communication systems
- computer networks
- computer systems
- computer vision
- data mining
- databases
- deep learning
- education
- Human-Computer Interaction (HCI)
- image processing
- information retrieval
- learning
- linguistics
- machine learning
- network protocols
- neural networks
- signal processing
Table of contents (41 papers)
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Applied Data Science: Social Good
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Applied Data Science: Healthcare
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Applied Data Science: E-Commerce and Finance
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. Applied Data Science and Demo Track
Book Subtitle: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V
Editors: Yuxiao Dong, Georgiana Ifrim, Dunja Mladenić, Craig Saunders, Sofie Van Hoecke
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-030-67670-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Softcover ISBN: 978-3-030-67669-8Published: 25 February 2021
eBook ISBN: 978-3-030-67670-4Published: 24 February 2021
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XLII, 577
Number of Illustrations: 24 b/w illustrations, 181 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Machine Learning, Computers and Education, Computer Appl. in Social and Behavioral Sciences, Computer Systems Organization and Communication Networks