UID:
almahu_9948254185202882
Umfang:
X, 229 p. 109 illus., 90 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2020.
ISBN:
9783030390983
Serie:
Lecture Notes in Artificial Intelligence ; 11986
Inhalt:
This 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. .
Anmerkung:
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.
In:
Springer eBooks
Weitere Ausg.:
Printed edition: ISBN 9783030390976
Weitere Ausg.:
Printed edition: ISBN 9783030390990
Sprache:
Englisch
DOI:
10.1007/978-3-030-39098-3
URL:
https://doi.org/10.1007/978-3-030-39098-3
