Call for papers: 2024 Explainable Online Learning for Uncertain Data Streams (OLUD 2024)

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 2024 Explainable Online Learning for Uncertain Data Streams  (OLUD 2024)

within the IEEE International Conference on Evolving and Adaptive Intelligent Systems 2024 (IEEE EAIS 2024)

Madrid, Spain, 23-24 May, 2024

   https://sites.google.com/view/olud/home

The key research questions addressed in this Special Session are (i) how to obtain accurate and explainable models from uncertain data streams; and (ii) how to exploit uncertain reasoning to explain adaptive models at any time step better. 

The Special Session aims to bring together theorists and practitioners who apply lifelong learning methods for sequential (and uncertain) data analysis to exchange and discuss ideas that enrich traditional approaches, e.g., computational methods for static datasets. The special session gets together experts from different research communities including (but not limited to):

• Incremental learning from numerical, linguistic, or granular stream data

• Continual learning from streams of images or videos

• Incremental feature extraction or feature weighting

• Incremental model validation indices

• Recursive methods and scalability issues in Big data processing

• Uncertainty modeling

• Evolving deep neural networks

• Evolving fuzzy systems

• Evolving ensembles of models

**** I***IMPORTANT DATES ****

• Paper submission: January 22, 2024

• Notification of acceptance: March 1, 2024

• Final paper submission: March 20, 2024

• Conference starting date: May 23, 2024 

**** For further details, please refer to the EAIS 2024 conference website: Link

********* ORGANIZING COMMITTEE ****

• Gabriella Casalino, University of Bari, Italy

• Paulo Vitor Campos Souza, Fondazione Bruno Kessler,  Italy

• Katarzyna Kaczmarek-Majer, Polish Academy of Sci., Poland 

• Daniel Leite, University of Paderborn, Germany

• Gianluca Zaza, University of Bari, Italy