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[null,null,"Titolo",null,"Advanced Analytics and Learning on Temporal Data : 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers / / edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"3-030-39098-5"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 229 p. 109 illus., 90 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 11986"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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 "]
[{"$nulls":4},"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."]
[null,null,null,"Sommario/riassunto","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. ."]