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Machine Learning and Knowledge Discovery in Databases [electronic resource] : 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.

Contributor(s): Brefeld, Ulf [editor.] | Fromont, Elisa [editor.] | Hotho, Andreas [editor.] | Knobbe, Arno [editor.] | Maathuis, Marloes [editor.] | Robardet, Céline [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 11908Publisher: Cham : Springer International Publishing : Imprint: Springer, 2020Edition: 1st ed. 2020.Description: XXVIII, 804 p. 379 illus., 222 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030461331.Subject(s): 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 NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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