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AALTD@ECML 2022 : Workshop on Advanced Analytics and Learning on Temporal Data

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Link: https://project.inria.fr/aaltd22
 
When Sep 19, 2022 - Sep 23, 2022
Where Grenoble, France
Abstract Registration Due Jun 13, 2022
Submission Deadline Jun 20, 2022
Notification Due Jul 13, 2022
Categories    time series   machine learning   data mining   temporal data
 

Call For Papers

The 7th International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2022) will be held on the week of September 19-23, 2022, co-located with the ECML/PKDD hybrid conference (https://2022.ecmlpkdd.org). The aim of this workshop is to bring together researchers and experts in machine learning, data mining, pattern analysis and statistics and create a platform for sharing research challenges, as well as advancing the research on temporal data analysis. Analysis and learning from temporal data covers a wide scope of tasks including learning metrics, learning representations, unsupervised feature extraction, clustering, classification and interpretation.

Authors of selected papers will be invited for publication in a special volume in the Lecture Notes in Computer Science (LNCS) series (see last year’s edition here: https://link.springer.com/book/10.1007/978-3-030-91445-5)

Topics of Interest
-------------------
The workshop welcomes papers that cover, but are not limited to, one or several of the following topics:
• Temporal data clustering
• Classification and regression of univariate and multivariate time series
• Early classification of temporal data
• Deep learning for temporal data
• Learning representation for temporal data
• Metric and kernel learning for temporal data
• Modeling temporal dependencies
• Time series forecasting
• Time series annotation, segmentation and anomaly detection
• Spatial-temporal statistical analysis
• Functional data analysis methods
• Data streams
• Interpretable/explainable time-series analysis methods
• Dimensionality reduction, sparsity, algorithmic complexity and big data challenges
• Benchmarking and assessment methods for temporal data
• Applications, including bioinformatics, medical, energy consumption, etc, on temporal data.

We welcome contributions that address aspects including, but not limited to: novel techniques, innovative use and applications, techniques for the use of hybrid models. We also invite papers describing industry time series management platforms, in particular those that raise open questions for which there are no current off-the-shelf solutions.

Paper Submission
-------------------
Paper submission is managed through EasyChair (https://easychair.org/conferences/?conf=aaltd22) for the following two tracks:

• Oral presentation
• Poster session (including research in progress and demos)

Authors that would not want their papers to apply for possible oral presentation should inform the organizers at the time of submission. Submitted papers should be 6 to 16 pages long using the LNCS formatting style.

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