Advanced analytics and learning on temporal data : 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised selected papers /

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Bibliographic Details
Meeting name:	AALTD (Workshop) (4th : 2019 : Würzburg, Germany)
Imprint:	Cham : Springer, 2020.
Description:	1 online resource (x, 229 pages) : illustrations (some color)
Language:	English
Series:	Lecture notes in artificial intelligence Lecture notes in computer science ; 11986 LNCS sublibrary. SL 7, Artificial intelligence Lecture notes in computer science. Lecture notes in artificial intelligence. Lecture notes in computer science ; 11986. LNCS sublibrary. SL 7, Artificial intelligence.
Subject:	Time-series analysis -- Data processing -- Congresses. Machine learning -- Congresses. Temporal databases -- Congresses. Machine learning. Temporal databases. Time-series analysis -- Data processing. Conference papers and proceedings.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12604329

Hidden Bibliographic Details
Varying Form of Title:	AALTD 2019
Other authors / contributors:	Lemaire, Vincent. Malinowski, Simon. Bagnall, Anthony. Bondu, Alexis. Guyet, Thomas. Tavenard, Romain.
ISBN:	9783030390983 3030390985 9783030390976 3030390977 9783030390990 3030390993
Digital file characteristics:	text file PDF
Notes:	Includes author index.
Summary:	This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, 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.
Other form:	Print version: AALTD (Workshop) (4th : 2019 : Würzburg, Germany). Advanced analytics and learning on temporal data. Cham, Switzerland : Springer, [2020] 9783030390976
Standard no.:	10.1007/978-3-030-39 10.1007/978-3-030-39098-3 9783030390976

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