FYI, belief functions are one of the ways to describe uncertainty in AI From: Thierry Denoeux <thierry.deno...@utc.fr<mailto:thierry.deno...@utc.fr>> Sent: Monday, November 27, 2023 10:49 PM
-- ****** Call for Papers ****** https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fbfasociety.org%2FBelief2024%2F&data=05%7C01%7Cuai%40engr.orst.edu%7C493a2109b79943e9742208dbf066acbb%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638368096001837172%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=LoldTas2O94doF0d6MsMgi%2Bov7tTR6rUsmx%2Bjl7sAtg%3D&reserved=0<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fantiphishing.vadesecure.com%2Fv4%3Ff%3DZURHSDhnY0huQ2tPS3VZai6lZy1SHhe47JGme3-CBwDmMXZP62EKSkAkl2fLHLC7%26i%3DUjFaS240Z0dKSFlwcTFONryzE4mPTymHUwQg74LmcR4%26k%3Dxoyu%26r%3DMDk0SW9xRkhTVGYydkJlTFKs2NdxoDX_WvvD0k8xnyM%26s%3Dc0a6d8b9135ea0c9f801b905d6f897f617704b9cfadfa27ab64f256adc332a0a%26u%3Dhttps%253A%252F%252Fbfasociety.org%252FBelief2024%252F&data=05%7C01%7Cuai%40engr.orst.edu%7C493a2109b79943e9742208dbf066acbb%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638368096001837172%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=63FV8GGh6TEQ41YWM0BCRNy1h1z4CWOWACLxYfOzmc0%3D&reserved=0> The 8th International Conference on Belief Functions (BELIEF 2024) Dates: September 4th-6th, 2024 Location: Belfast, Ulster University, Northern Ireland, UK * April 15, 2024: Paper submission deadline * May 31, 2024: Author notification * June 30, 2024: Camera-ready copy due ================================================================ The theory of belief functions, also referred to as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty generalizing Bayesian probability theory. These early contributions have been the starting points of many important theoretical and practical developments. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and with applications in machine learning, statistical inference, information fusion, knowledge representation, risk analysis, etc. It has well understood connections with other frameworks such as probability, possibility and imprecise probability theories. The biennial BELIEF conferences (sponsored by the Belief Functions and Applications Society https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.bfasociety.org%2F&data=05%7C01%7Cuai%40engr.orst.edu%7C493a2109b79943e9742208dbf066acbb%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638368096001837172%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=bWX7iDYLCjjtXON578Y8IoxSzTe5T7IrstjAKjsCIko%3D&reserved=0<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fantiphishing.vadesecure.com%2Fv4%3Ff%3DZURHSDhnY0huQ2tPS3VZai6lZy1SHhe47JGme3-CBwDmMXZP62EKSkAkl2fLHLC7%26i%3DUjFaS240Z0dKSFlwcTFONryzE4mPTymHUwQg74LmcR4%26k%3Dxoyu%26r%3DMDk0SW9xRkhTVGYydkJlTFKs2NdxoDX_WvvD0k8xnyM%26s%3D9172a22c0a6346fb94bd02e423e5684d7a1b72dc2b2be24e986816b011426a69%26u%3Dhttps%253A%252F%252Fwww.bfasociety.org%252F&data=05%7C01%7Cuai%40engr.orst.edu%7C493a2109b79943e9742208dbf066acbb%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638368096001837172%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Fkv9Oni%2BgjUL8k2TDfMDTKD9KezCd0fpjSSX%2BaevjYk%3D&reserved=0>) are dedicated to the confrontation of ideas, the reporting of recent achievements and the presentation of the wide range of applications of this theory. Previous editions of this conference series were held in Brest, France (2010); in Compiègne, France (2012); in Oxford, UK (2014); in Prague, Czech Republic (2016); in Compiègne, France (2018); in Shanghai, China (2021); and in Paris, France (2022). The Eighth International Conference on Belief Functions (BELIEF 2024) will be held in Belfast, Northern Ireland, UK, on September 4th-6th, 2024. To support cross-fertilization among researchers working in different subfields of AI and related disciplines, tutorials and special sessions will be proposed and dedicated to the links between machine learning and uncertain reasoning, including topics such as quantification of prediction uncertainty, fusion rules for ensemble learning, belief propagation over deep neural networks, links with explainable and symbolic AI, etc. Submissions of papers combining several of these topics, or more generally at the cross-road of belie functions and other AI methods or uncertainty theories, along with relevant applications, are welcome. =========== Proceedings =========== Proceedings of the previous editions of BELIEF have been published by Springer-Verlag as volumes of the Lecture Notes in Artificial Intelligence (LNCS/LNAI) series and indexed by: ISI Web of Science; EI Engineering Index; ACM Digital Library; dblp; Google Scholar; IO-Port; MathSciNet; Scopus; Zentralblatt MATH. The Springer-Verlag has confirmed that the BELIEF2024’s proceedings will be continually published in the Lecture Notes in Artificial Intelligence (LNCS/LNAI). ================== IJAR Special issue ================== Authors of selected papers from the BELIEF 2024 conference will be invited to submit extended versions of their papers for possible inclusion in a special issue of the International Journal of Approximate Reasoning. ======================================= BELIEF 2024 Program Committee co-chairs ======================================= Dr Yaxin Bi (y...@ulster.ac.uk<mailto:y...@ulster.ac.uk>), Ulster University, UK Dr Anne-Laure Jousselme (anne-laure.jousse...@csgroup.eu<mailto:anne-laure.jousse...@csgroup.eu>), CS Group, France ---------- ---------- Prof. Thierry Denoeux Université de technologie de Compiègne Institut universitaire de France Rue Roger Couttolenc, CS 60319 60203 Compiègne cedex, France https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.hds.utc.fr%2F~tdenoeux&data=05%7C01%7Cuai%40engr.orst.edu%7C493a2109b79943e9742208dbf066acbb%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638368096001837172%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=s%2FYGWmhqDeJLVlCqrUh%2F00m%2Ff1AyOZe5UdoQW5FEpBQ%3D&reserved=0
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