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AALTD 2024 : 9th International Workshop on Advanced Analytics and Learning on Temporal Data | |||||||||||||||||
Link: https://ecml-aaltd.github.io/aaltd2024/ | |||||||||||||||||
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Call For Papers | |||||||||||||||||
AALTD 2024: CALL FOR PAPERS
https://ecml-aaltd.github.io/aaltd2024/ ################################################################################ The 9th International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2024) will be held on the week of September 9, 2024, co-located with the ECML/PKDD 2024 conference (https://2024.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, segmentation and interpretation. The AALTD 2024 workshop is also happy to highlight a connected ECML/PKDD tutorial, which focuses on the Aeon library for working with temporal data. Details about the tutorial can be found at An Introduction to Machine Learning from Time Series. 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 Modelling 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 CMT (login and select ECMLPKDDWorkshops2024, then click on Create new submission and select 9th Workshop on Advanced Analytics and Learning on Temporal Data (AALTD) at ECML-PKDD 2024). There are two submission tracks: • Oral presentation • Poster session (including research in progress and demos) Submissions will be double-blind (anonymised) and reviewed by at least 2 program committee members. Authors that would not want their papers to apply for possible oral presentation should inform the organisers at the time of submission. Submitted papers should be 6 to 16 pages long using the LNCS formatting style. After the workshop, 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). Important Dates Abstract submission deadline: June 14, 2024 Paper submission deadline: June 21, 2024 Acceptance notification: July 15, 2024 Camera-ready deadline: July 30, 2024 Workshop date: Week of September 9, 2024, TBD Organizers Tony Bagnall, University of East Anglia, England Thomas Guyet, Inria, France Georgiana Ifrim, University College Dublin, Ireland Vincent Lemaire, Orange Labs, France Simon Malinowski, Université de Rennes 1/IRISA, France Patrick Schäfer: Humboldt University of Berlin, Germany Romain Tavenard: Université de Rennes 2, IRISA/LETG, France Contact If you have any questions about this workshop please contact georgiana.ifrim@ucd.ie and patrick.schaefer@hu-berlin.de |
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