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Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers: Lecture Notes in Computer Science, cartea 12588

Editat de Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim
en Limba Engleză Paperback – 16 dec 2020
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.
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Specificații

ISBN-13: 9783030657413
ISBN-10: 3030657418
Pagini: 233
Ilustrații: X, 233 p. 88 illus., 67 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.35 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.- Bio-Informatics, Medical, Energy Consumption, Temporal Data.