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N� de ref. del art�culo 6545-9783030461492

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Detalles bibliogr�ficos

T�tulo: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, W�rzburg, Germany, September 16?20, 2019, Proceedings, . (Lecture Notes in Computer Science, 11906)
Editor: Springer -
Fecha de publicaci�n: 2020
Idioma: Ingl�s
ISBN 10: 3030461491
ISBN 13: 9783030461492
Encuadernaci�n: paperback
Estado: Very Good

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Sinopsis

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 W�rzburg, 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.

De la contraportada

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.

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