E-Book, Englisch, Band 11986, 229 Seiten, eBook
4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers
E-Book, Englisch, Band 11986, 229 Seiten, eBook
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-030-39098-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Robust 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.