Advanced Analytics and Learning on Temporal Data : 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers

Vincent Lemaire

ISBN 10: 3030657418 / ISBN 13: 9783030657413

Edité par Springer International Publishing, 2020

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020.The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.

N° de réf. du vendeur 9783030657413

Détails bibliographiques

• Titre: Advanced Analytics and Learning on Temporal Data : 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
• Éditeur: Springer International Publishing
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 3030657418
• ISBN à 13 chiffres: 9783030657413
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 14 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 14 millimètres de profondeur
• Poids: 376 grammes

A propos de ce titre

Synopsis

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020.

The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.