Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019 : proceedings
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Bibliographic Information
Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019 : proceedings
（Lecture notes in computer science, 11906-11908 . Lecture notes in artificial intelligence . LNCS sublibrary ; SL7 . Artificial intelligence）
Springer, c2020
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- pt. 2
- pt. 3
- Other Title
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ECML PKDD 2019
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Other editors: Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet
Includes bibliographical references and index
Description and Table of Contents
- Volume
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pt. 3 ISBN 9783030461324
Description
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 Wurzburg, 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.
Table of 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.
- Volume
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pt. 2 ISBN 9783030461461
Description
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 Wurzburg, 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.
Chapter "Incorporating Dependencies in Spectral Kernels for Gaussian Processes" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Table of Contents
Supervised Learning.- Multi-Label Learning.- Large-Scale Learning.- Deep Learning.- Probabilistic Models.- Natural Language Processing.
- Volume
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pt. 1 ISBN 9783030461492
Description
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 Wurzburg, 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.
Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Table of Contents
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.
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