Description: Advanced Analytics and Learning on Temporal Data : 5th Ecml Pkdd Workshop, Aaltd 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers, Paperback by Lemaire, Vincent (EDT), ISBN 3030657418, ISBN-13 9783030657413, Like New Used, Free shipping in the US 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.
Price: 62.68 USD
Location: Jessup, Maryland
End Time: 2025-02-04T21:45:29.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Return policy details:
Book Title: Advanced Analytics and Learning on Temporal Data : 5th Ecml Pkdd
Number of Pages: X, 233 Pages
Publication Name: Advanced Analytics and Learning on Temporal Data : 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
Language: English
Publisher: Springer International Publishing A&G
Publication Year: 2020
Subject: Probability & Statistics / General, Intelligence (Ai) & Semantics, General, Databases / Data Mining
Type: Textbook
Item Weight: 16 Oz
Author: Simon Malinowski
Subject Area: Mathematics, Computers, Science
Item Length: 9.3 in
Series: Lecture Notes in Computer Science Ser.
Item Width: 6.1 in
Format: Trade Paperback
