Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019 : proceedings

著者

    • Brefeld, Ulf
    • Fromont, Elisa
    • Hotho, Andreas
    • Knobbe, Arno
    • Maathuis, Marloes
    • Robardet, Céline

書誌事項

Machine learning and knowledge discovery in databases : European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019 : proceedings

Ulf Brefeld ... [et al.] (Eds.)

（Lecture notes in computer science, 11906-11908 . Lecture notes in artificial intelligence . LNCS sublibrary ; SL7 . Artificial intelligence）

Springer, c2020

  • pt. 1
  • pt. 2
  • pt. 3

タイトル別名

ECML PKDD 2019

大学図書館所蔵 件 / 全1件

この図書・雑誌をさがす

注記

Other editors: Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet

Includes bibliographical references and index

内容説明・目次

巻冊次

pt. 3 ISBN 9783030461324

内容説明

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.

目次

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.
巻冊次

pt. 2 ISBN 9783030461461

内容説明

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.

目次

Supervised Learning.- Multi-Label Learning.- Large-Scale Learning.- Deep Learning.- Probabilistic Models.- Natural Language Processing.
巻冊次

pt. 1 ISBN 9783030461492

内容説明

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.

目次

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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