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OverviewThis book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover 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, on temporal data. Full Product DetailsAuthor: Vincent Lemaire , Simon Malinowski , Anthony Bagnall , Alexis BonduPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: 1st ed. 2020 Volume: 11986 Weight: 0.454kg ISBN: 9783030390976ISBN 10: 3030390977 Pages: 229 Publication Date: 23 January 2020 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsRobust Functional Regression for Outlier Detection.- Transform Learning Based Function Approximation for Regression and Forecasting.- Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data.- A fully automated periodicity detection in time series.- Conditional Forecasting of Water Level Time Series with RNNs.- Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories.- Localized Random Shapelets.- Feature-Based Gait Pattern Classification for a Robotic Walking Frame.- How to detect novelty in textual data streams? A comparative study of existing methods.- Seq2VAR: multivariate time series representation with relational neural networks and linear autoregressive model.- Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets.- Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems.- Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets using Deep Learning.- Learning Stochastic Dynamical Systems via Bridge Sampling.- Quantifying Quality of Actions Using Wearable Sensor.- An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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