Description: Advanced Analytics and Learning on Temporal Data Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). 4th ECML PKDD Workshop, AALTD 2019, W?rzburg, Germany, September 20, 2019, Revised Selected Papers Author(s): Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard Format: Paperback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030390976, 978-3030390976 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 W?rzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover 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, on temporal data. ?
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Location: Aldershot
End Time: 2025-01-21T11:44:16.000Z
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Book Title: Advanced Analytics and Learning on Temporal Data
Number of Pages: 229 Pages
Publication Name: Advanced Analytics and Learning on Temporal Data: 4th ECML PKDD Workshop, AALTD 2019, Wurzburg, Germany, September 20, 2019, Revised Selected Papers
Language: English
Publisher: Springer Nature Switzerland A&G
Item Height: 235 mm
Subject: Engineering & Technology, Computer Science
Publication Year: 2020
Type: Textbook
Item Weight: 373 g
Author: Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Romain Tavenard, Thomas Guyet, Alexis Bondu
Item Width: 155 mm
Series: Lecture Notes in Artificial Intelligence
Format: Paperback
