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Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2019, Wurzburg, Germany, September 16–20, 2019, Proceedings, Part III (Lecture Notes in Computer Science)

By: Andreas Hotho (Edited by) , Arno Knobbe (Edited by) , Celine Robardet (Edited by) , Elisa Fromont (Edited by) , Marloes Maathuis (Edited by) , Ulf Brefeld (Edited by)

Extended Catalogue

Ksh 10,250.00

Format: Paperback or Softback

ISBN-10: 3030461327

ISBN-13: 9783030461324

Collection / Series: Lecture Notes in Computer Science

Collection Type: Publisher collection

Edition statement: 2020 ed.

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: May 1st, 2020

Publication Status: Active

Product extent: 804 Pages

Product Classification / Subject(s): Databases
Computer networking & communications
Machine learning

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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;
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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