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Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part III / edited by Ulf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11908
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 11908
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Application software.
- Database management.
- Computers.
- Computer engineering.
- Computer networks.
- Artificial Intelligence.
- Computer and Information Systems Applications.
- Database Management System.
- Computing Milieux.
- Computer Engineering and Networks.
- Local Subjects:
- Artificial Intelligence.
- Computer and Information Systems Applications.
- Database Management System.
- Computing Milieux.
- Computer Engineering and Networks.
- Physical Description:
- 1 online resource (XXVIII, 804 pages) : 379 illustrations, 222 illustrations in color.
- Edition:
- 1st edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- The three volume proceedings LNAI 11906 - 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization. Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing. Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track.
- Contents:
- Reinforcement Learning and Bandits
- Ranking
- Applied Data Science: Computer Vision and Explanation
- Applied Data Science: Healthcare
- Applied Data Science: E-commerce, Finance, and Advertising
- Applied Data Science: Rich Data
- Applied Data Science: Applications
- Demo Track.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-46133-1
- 9783030461331
- Access Restriction:
- Restricted for use by site license.
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