Advanced Analytics and Learning on Temporal Data, (9783032155344) — Readings Books
Advanced Analytics and Learning on Temporal Data
Paperback

Advanced Analytics and Learning on Temporal Data

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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

This book constitutes the revised selected papers of the 10th ECML PKDD workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2025, held in Porto, Portugal, on September 19, 2025.

The 13 full papers presented here were carefully reviewed and selected from 22 submissions. The papers focus on the following topics: Clustering and Analysis of Time Series; Forecasting and Prediction; Analysis and Processing of Time Series; Models and Approaches Based on Deep Learning and LLMs; Time Series Classification; Augmentation, Imputation, and Preprocessing Techniques.

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Format
Paperback
Publisher
Springer Nature Switzerland AG
Country
CH
Date
21 February 2026
Pages
215
ISBN
9783032155344

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

This book constitutes the revised selected papers of the 10th ECML PKDD workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2025, held in Porto, Portugal, on September 19, 2025.

The 13 full papers presented here were carefully reviewed and selected from 22 submissions. The papers focus on the following topics: Clustering and Analysis of Time Series; Forecasting and Prediction; Analysis and Processing of Time Series; Models and Approaches Based on Deep Learning and LLMs; Time Series Classification; Augmentation, Imputation, and Preprocessing Techniques.

Read More
Format
Paperback
Publisher
Springer Nature Switzerland AG
Country
CH
Date
21 February 2026
Pages
215
ISBN
9783032155344