Tekijä: Vincent Lemaire (ed.); Simon Malinowski (ed.); Anthony Bagnall (ed.); Thomas Guyet (ed.); Romain Tavenard (ed.); Geo Ifrim Kustantaja: Springer (2020) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Vincent Lemaire (ed.); Simon Malinowski (ed.); Anthony Bagnall (ed.); Thomas Guyet (ed.); Romain Tavenard (ed.); Geo Ifrim Kustantaja: Springer (2021) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Thomas Guyet; Georgiana Ifrim; Simon Malinowski; Anthony Bagnall; Patrick Shafer; Vincent Lemaire Kustantaja: Springer International Publishing AG (2023) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Vincent Lemaire (ed.); Simon Malinowski (ed.); Anthony Bagnall (ed.); Alexis Bondu (ed.); Thomas Guyet (ed.); Rom Tavenard Kustantaja: Springer (2020) Saatavuus: Noin 17-20 arkipäivää
Tekijä: Georgiana Ifrim; Romain Tavenard; Anthony Bagnall; Patrick Schaefer; Simon Malinowski; Thomas Guyet; Vincent Lemaire Kustantaja: Springer International Publishing AG (2023) Saatavuus: Noin 17-20 arkipäivää
EUR 65,00
Advanced Analytics and Learning on Temporal Data : 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revis
Springer Sivumäärä: 233 sivua Asu: Pehmeäkantinen kirja Julkaisuvuosi: 2020, 16.12.2020 (lisätietoa) Kieli: Englanti
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.
