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[Apologies for cross postings] ******************************************************** CALL FOR PAPERS - KES 2023 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems http://kes2023.kesinternational.org 6-8 September 2023 | Athens, Greece Since it's inception 27 years ago, the International Conference on Knowledge-Based and Intelligent Information & Engineering Systems has been the go-to event for exploring intelligent systems and their applications. With more over 450 attendees and 5 expert speakers in 2022, the annual KES Conference unites our community to connect, educate, inspire and grow. We are honored to invite you to submit a paper to share your expertise with our community. KES-23 will take place in Athens, Greece from 6-8 September 2023. The conference encompasses a broad spectrum of intelligent systems related subjects. *IMPORTANT* - Full papers should be detailed academic articles in conventional format. (there is no abstract submission stage) The guide length for full papers is 8 to 10 pages (maximum). DEADLINES FOR SUBMISSIONS Submission of papers Deadline: The deadline to submit your paper is 3 April, 2023. Notification of Acceptance: Your submission will be evaluated by 08 May, 2023. Final Publication Files: Your publication files to be received by 29 May, 2023. G1: Machine Learning, Artificial Neural Networks and Deep Learning This track will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning in different application fields with especial emphasis on the design of those systems, are particularly encouraged. The topics of interest include (but are not limited to): * computational learning theory * cooperative learning * federated Learning and distributed IA * distributed and parallel learning algorithms and applications * feature extraction and classification * hybrid learning algorithms * inductive learning * instance-based learning * knowledge discovery in databases * knowledge intensive learning * learning through mobile data mining * machine learning and information retrieval * machine learning for web navigation and mining * multi-strategy learning * neural network learning * online and incremental learning * reinforcement learning * scalability of learning algorithms * statistical learning * text and multimedia mining through machine learning * machine learning for natural language processing Best regards, [X] Ahmed SAMET Asso. prof in computer science at INSA Strasbourg ahmed.sa...@insa-strasbourg.fr <mailto:%20ahmed.sa...@insa-strasbourg.fr> http://ahmed.samet.free.fr [X]
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