Advanced analytics and learning on temporal data : 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised selected papers
- Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard (eds.).
- text file
- Cham : Springer, 2020.
- Physical description
- 1 online resource (x, 229 pages) : illustrations (some color)
- Lecture notes in computer science. Lecture notes in artificial intelligence.
- Lecture notes in computer science ; 11986.
- LNCS sublibrary. SL 7, Artificial intelligence.
- 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.
- 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.
- Time-series analysis > Data processing > Congresses.
- Machine learning > Congresses.
- Temporal databases > Congresses.
- Série chronologique > Informatique > Congrès.
- Apprentissage automatique > Congrès.
- Bases de données spatio-temporelles > Congrès.
- Computer networking & communications.
- Information technology: general issues.
- Computer vision.
- Artificial intelligence.
- Computers > Online Services > General.
- Computers > Networking > General.
- Computers > Data Processing.
- Computers > Computer Vision & Pattern Recognition.
- Computers > Intelligence (AI) & Semantics.
- Machine learning.
- Temporal databases.
- Time-series analysis > Data processing.
- Publication date
- Title variation
- AALTD 2019
- Lecture notes in artificial intelligence
- Lecture notes in computer science ; 11986
- LNCS sublibrary. SL 7, Artificial intelligence
- Includes author index.
- 9783030390983 (electronic bk.)
- 3030390985 (electronic bk.)
- 9783030390976 (print)
- 9783030390990 (print)
- 3030390993 (print)