Archive for the ‘Congress’ Category

ML4CPS in Hamburg – Deadline Extension

Please note that the Deadline for submission of full papers for ML4CPS – Machine Learning for Cyber-Physical Systems – 2023 in Hamburg has been extended to the 20th of January. Furthermore, we now also accept short papers. The Deadline for short papers will be the 27th of January.   We aim to bring together researchers […]

Fwd: [CVML] CfP: C-MAS2023: The First International Workshop on Citizen-Centric Multiagent Systems

  C-MAS2023: The First International Workshop on Citizen-Centric Multiagent Systems  (held during AAMAS 2023, London, 29th or 30th May 2023)   Webpage: https://sites.google.com/view/cmas23     Large-scale AI systems promise to address important societal challenges, such as decarbonising our energy system, transitioning to on-demand mobility or responding effectively to disasters. However, citizen end users are often seen […]

Call for Papers Special Issue on Deep Learning for Anomaly Detection

  Dear Colleagues,  I am contacting you in my capacity as Guest Editor for a Special Issue titled: “Deep Learning for Anomaly Detection” to appear in “Algorithms” MDPI journal: https://www.mdpi.com/journal/algorithms/special_issues/Y072QR9GTI With this call for papers, I invite you and/or your co-authors to submit an original research paper, or a focused review, for our special issue. Deadline for manuscript submissions: 30 August […]

Machine Learning, Artificial Neural Networks and Deep Learning@KES2023

********************************************************   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 […]

ICLR 2023 Workshop on Domain Generalization

  ICLR 2023 Workshop: What do we need for successful domain generalization? Website: https://domaingen.github.io/ The real challenge for any machine learning system is to be reliable and robust in any situation, even if it is different compared to training conditions. Existing general purpose approaches to domain generalization (DG) — a problem setting that challenges a […]

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