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AALTD@ECML 2023 : International Workshop on Advanced Analytics and Learning on Temporal Data | |||||||||||||||||
Link: https://ecml-aaltd.github.io/aaltd2023/ | |||||||||||||||||
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Call For Papers | |||||||||||||||||
The 8th International Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2023) will be held on the week of September 18, 2023, co-located with the ECML/PKDD 2023 conference (https://2023.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 2023 workshop is also organising a ECML/PKDD discovery challenge, which focuses on Human Activity Segmentation. Details about the challenge can be found at https://2023.ecmlpkdd.org/submissions/discovery-challenge/challenges/ 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 ECMLPKDDworkshop2023, then click on Create new submission and select 8th Workshop on Advanced Analytics and Learning on Temporal Data (AALTD) at ECML-PKDD 2023). 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 12, 2023 • Paper submission deadline: June 19, 2023 • Acceptance notification: July 12, 2023 • Camera-ready deadline: July 30, 2023 • Workshop date: Week of September 18, 2023, 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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