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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 / edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 12588
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 12588
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Data mining.
- Social sciences-Data processing.
- Machine learning.
- Education-Data processing.
- Computer networks.
- Artificial Intelligence.
- Data Mining and Knowledge Discovery.
- Computer Application in Social and Behavioral Sciences.
- Machine Learning.
- Computers and Education.
- Computer Communication Networks.
- Local Subjects:
- Artificial Intelligence.
- Data Mining and Knowledge Discovery.
- Computer Application in Social and Behavioral Sciences.
- Machine Learning.
- Computers and Education.
- Computer Communication Networks.
- Physical Description:
- 1 online resource (X, 233 pages) : 88 illustrations, 67 illustrations in color.
- Edition:
- 1st ed. 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- 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 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.
- 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.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-65742-0
- 9783030657420
- Access Restriction:
- Restricted for use by site license.
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