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

by Vincent Lemaire (Editor), Simon Malinowski (Editor), Anthony Bagnall (Editor), Thomas Guyet (Editor), Romain Tavenard (Editor)

Overview

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.

Product Details

ISBN-13:	9783030657413
Publisher:	Springer International Publishing
Publication date:	12/15/2020
Series:	Lecture Notes in Computer Science , #12588
Edition description:	1st ed. 2020
Pages:	233
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

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.