Call for Papers |
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Learning from Temporal Data ----------------------------- Temporal information is all around us. Numerous important fields, including weather and climate, ecology, transport, urban computing, bioinformatics, medicine, and finance routinely deal with temporal data. Temporal data present a number of new challenges, including increased dimensionality, drifts, complex behavior in terms of long-term interdependence and temporal sparsity, to mention a few. Hence, learning from temporal data requires specialized strategies that are different from those used for static data. Continuous cross-domain knowledge exchange is required since many of these difficulties cut over the lines separating various fields. This workshop aims to integrate the research on learning from temporal data from various areas and to synthesize new concepts based on statistical analysis, time series analysis, graph analysis, signal processing, and machine learning. ----------------------------- Guest editors ----------------------------- João Mendes-Moreira Joydeep Chandra Albert Bifet ----------------------------- Topics of interest: ----------------------------- 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 transport, urban computing, weather and climate, ecology, bio-informatics, medical, energy consumption, on temporal data ----------------------------- Important dates: ----------------------------- Submission due date: 17/11/2023 Decision due date: 16/02/2024 Submission of revisions: 15/03/2024 Final decisions: 19/04/2024 Publication date: May 2024 ----------------------------- General inquiry contacts ----------------------------- João Mendes Moreira ([email protected]) ----------------------------- Submission and general inquiries ----------------------------- The JDSA Associate EIC, editorial board, or staff. |
Credits and Sources |
| [1] JDSA-LearnTeD 2024 : JDSA special isssue on Learning from Temporal data |
