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Advanced Analytics and Learning on Temporal Data

4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Vincent Lemaire

    1. Orange Labs, Lannion, France

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  2. Simon Malinowski

    1. Inria, University of Rennes, Rennes, France

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  3. Anthony Bagnall

    1. University of East Anglia, Norwich, UK

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  4. Alexis Bondu

    1. Orange Labs, Châtillon, France

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  5. Thomas Guyet

    1. Irisa, Agrocampus Ouest, Rennes, France

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  6. Romain Tavenard

    1. University of Rennes 2, Rennes, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11986)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: AALTD 2019.

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Table of contents (16 papers)

  1. Front Matter

    Pages i-x
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  2. Oral Presentation

    1. Front Matter

      Pages 1-1
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    2. Robust Functional Regression for Outlier Detection

      • Harjit Hullait, David S. Leslie, Nicos G. Pavlidis, Steve King
      Pages 3-13

    3. Transform Learning Based Function Approximation for Regression and Forecasting

      • Kriti Kumar, Angshul Majumdar, M. Girish Chandra, A. Anil Kumar
      Pages 14-25

    4. Proactive Fiber Break Detection Based on Quaternion Time Series and Automatic Variable Selection from Relational Data

      • Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot, Fabrice Clérot
      Pages 26-42

    5. A Fully Automated Periodicity Detection in Time Series

      • Tom Puech, Matthieu Boussard, Anthony D’Amato, Gaëtan Millerand
      Pages 43-54

    6. Conditional Forecasting of Water Level Time Series with RNNs

      • Bart J. van der Lugt, Ad J. Feelders
      Pages 55-71

    7. Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories

      • Marieke Vinkenoog, Mart Janssen, Matthijs van Leeuwen
      Pages 72-84

    8. Localized Random Shapelets

      • Mael Guillemé, Simon Malinowski, Romain Tavenard, Xavier Renard
      Pages 85-97

  3. Poster Presentation

    1. Front Matter

      Pages 99-99
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    2. Feature-Based Gait Pattern Classification for a Robotic Walking Frame

      • Christopher M. A. Bonenberger, Benjamin Kathan, Wolfgang Ertel
      Pages 101-109

    3. How to Detect Novelty in Textual Data Streams? A Comparative Study of Existing Methods

      • Clément Christophe, Julien Velcin, Jairo Cugliari, Philippe Suignard, Manel Boumghar
      Pages 110-125

    4. Seq2VAR: Multivariate Time Series Representation with Relational Neural Networks and Linear Autoregressive Model

      • Edouard Pineau, Sébastien Razakarivony, Thomas Bonald
      Pages 126-140

    5. Modelling Patient Sequences for Rare Disease Detection with Semi-supervised Generative Adversarial Nets

      • Kezi Yu, Yunlong Wang, Yong Cai
      Pages 141-150

    6. Extended Kalman Filter for Large Scale Vessels Trajectory Tracking in Distributed Stream Processing Systems

      • Katarzyna Juraszek, Nidhi Saini, Marcela Charfuelan, Holmer Hemsen, Volker Markl
      Pages 151-166

    7. Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets Using Deep Learning

      • Yildiz Karadayi
      Pages 167-182

    8. Learning Stochastic Dynamical Systems via Bridge Sampling

      • Harish S. Bhat, Shagun Rawat
      Pages 183-198

    9. Quantifying Quality of Actions Using Wearable Sensor

      • Mohammad Al-Naser, Takehiro Niikura, Sheraz Ahmed, Hiroki Ohashi, Takuto Sato, Mitsuhiro Okada et al.
      Pages 199-212

    10. An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis

      • Daniel Shen, Min Chi
      Pages 213-228

  4. Back Matter

    Pages 229-229
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  1. Advanced Analytics and Learning on Temporal Data

Keywords

About this book

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.

 

Editors and Affiliations

  • Orange Labs, Lannion, France

    Vincent Lemaire

  • Inria, University of Rennes, Rennes, France

    Simon Malinowski

  • University of East Anglia, Norwich, UK

    Anthony Bagnall

  • Orange Labs, Châtillon, France

    Alexis Bondu

  • Irisa, Agrocampus Ouest, Rennes, France

    Thomas Guyet

  • University of Rennes 2, Rennes, France

    Romain Tavenard

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