Cover image for Advanced Analytics and Learning on Temporal Data 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers
Title:
Advanced Analytics and Learning on Temporal Data 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers
Author:
Ifrim, Georgiana. editor.
ISBN:
9783031498961
Edition:
1st ed. 2023.
Physical Description:
XIII, 308 p. 113 illus., 90 illus. in color. online resource.
Series:
Lecture Notes in Artificial Intelligence, 14343
Contents:
Human Activity Segmentation Challenge -- Human Activity Segmentation Challenge@ECML/PKDD'23 -- Change points detection in multivariate signal applied to human activity segmentation -- Change Point Detection via Synthetic Signals -- Oral Presentation -- Clustering time series with k-medoids based algorithms -- Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting -- RED CoMETS: an ensemble classifier for symbolically represented multivariate time series -- Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving -- Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression -- ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging -- Poster Presentation -- Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks -- Evaluating Explanation Methods for Multivariate Time Series Classification -- tGLAD: A sparse graph recovery based approach for multivariate time series segmentation -- Designing a New Search Space for Multivariate Time-Series Neural Architecture Search -- Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms -- Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Behaviours and Detect Health Issues -- Exploiting Context and Attention with Recurrent Neural Network for Sensor Time Series Prediction -- Rail Crack Propagation Forecasting Using Multi-horizons RNNs -- Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies -- Time-aware Predictions of Moments of Change in Longitudinal User Posts on Social Media.
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