- SIPTA News - lists.sipta.org

ISIPTA seminar: errata (Babara Vantaggi, 26th March)
by sdesterc 20 Mar '24

20 Mar '24

Dear Colleagues, You will probably have corrected this yourself, but due to an autocorrect function and my own impatience to announce the seminar, there was a mistake in the title date and in the name of our esteemed speaker. This is, and will be a talk by Barbara Vantaggi, on the 26th of March, at 3pm Paris time. Best regards, and sorry for any incovenience. Sébastien

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Next SIPTA seminar: Barbara Vantage (IP and finance), 16th March at 3pm Paris time.
by sdesterc 20 Mar '24

20 Mar '24

Dear colleagues, We are delighted to announce our upcoming SIPTA online seminar on imprecise probabilities (IP). These monthly events are open to anyone interested in IP, and will be followed by a Q&A and open discussion. They also provide an occasion for the community to meet, keep in touch and exchange between in-person events. The next seminar will take place on the 26th of March (Tuesday). The zoom link for this seminar is https://utc-fr.zoom.us/j/86044393366 For this new seminar, we are very happy to have Barbara Vantaggi as our speaker. Barbara Vantage is a Full Professor of Mathematical Methods of Economics, Finance and Actuarial Sciences at the University La Sapienza, Roma. She is well-known for her many contributions to the foundations of (imprecise) probabilistic reasoning under coherence, decision making under uncertainty and their development to financial applications. On the 26th of March at 15:00 CEST:paris time (up to 17:00 CEST, with a talk duration of 45min/1h), she will talk about "A dynamic Choquet pricing rule with bid-ask spreads under Dempster–Shafer uncertainty”, showing how imprecise probabilistic approaches can be useful in financial mathematics. Curious? Then check out the abstract on the webpage of the SIPTA seminars: sipta.org/events/sipta-seminars. The zoom link for attending the seminar can be found on that same page, where you will also find announcements of our next seminars. So please mark your calendars on the 26th of March, and join us for the occasion. And for those who missed the previous seminar and want to catch up, or simply want to see it again and again, it is online at https://www.youtube.com/watch?v=LG4trFXC53g See you at the seminar! Sébastien, Enrique and Jasper

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BELIE 2024 - Call for Papers
by Bi, Yaxin 18 Mar '24

18 Mar '24

****** Call for Papers ****** https://bfasociety.org/Belief2024/ The 8th International Conference on Belief Functions (BELIEF 2024) New Dates: September 2nd-4th, 2024 (updated) 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 ================================================================ Keynote speakers: Professor Zhi-Hua Zhou, Nanjing University, China Professor Prakash P. Shenoy, University of Kansas, United States Professor Frederic Pichon, Artois University, France ================================================================ Early Bird Registration Open Until: 22nd July 2024 Early Bird Registration: £325 (€380) Regular Registration: £375 (€440) Early Bird Student Registration: £225 (€265) Student Registration: £275 (€325) ================================================================ 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://www.bfasociety.org/) 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 2nd-4th, 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.bi(a)ulster.ac.uk<mailto:y.bi@ulster.ac.uk>), Ulster University, UK Dr Anne-Laure Jousselme (anne-laure.jousselme(a)csgroup.eu<mailto:anne-laure.jousselme@csgroup.eu>), CS Group, France This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Deadline Extended - 1st International Workshop on Trustworthy and eXplainable Artificial Intelligence for Networks (TX4Nets)
by Cristina Rottondi 14 Mar '24

14 Mar '24

Dear colleagues, I'm sharing the updated CfP of thTX4Nets workshop, with extended submission deadline to April 14. Contributions on uncertainty quantification applied to telecommunication networks are welcome. Best regards, Cristina Rottondi ***Please accept our apologies if you receive multiple copies of this call for paper*** ------------------- 1st International Workshop on Trustworthy and eXplainable Artificial Intelligence for Networks (TX4Nets) co-located with IFIP Networking 2024<https://networking.ifip.org/2024/index.php/> Thessaloniki, Greece, 3-6 June 2024 Link to the official workshop website: https://sites.google.com/view/tx4nets2024 ------------------- *** TX4Nets 2024 CALL FOR PAPER *** link to CFP: https://sites.google.com/view/tx4nets2024/call-for-papers Aim and Scope In light of next communication networks characterized by zero-touch network management, network operators have started the deployment of automated AI-based frameworks addressing various use cases including resource allocation, failure prediction and identification, traffic prediction. However, these deployments predominantly function as black boxes, with practitioners unable to comprehend the internal reasoning or decision processes of these automated AI-based frameworks. In this context, eXplainable Artificial Intelligence (XAI) emerges as a promising collection of frameworks and technologies designed to enhance the transparency of black-box models. XAI achieves this by providing explanations for the decisions made, enabling practitioners to eliminate bias influencing models, understand when to trust or distrust model decisions, and gain insights into the problem at hand. In addition to this, it also becomes of paramount importance to design and adopt models and methods that are inherently able to quantify their uncertainty in taking decisions based on conformal prediction. This, in turn, facilitates a reliable and Trustworthy deployment of machine learning and Artificial Intelligence models. While the application of Trustworthy and Explainable Artificial Intelligence has been extensively explored in diverse domains such as healthcare and finance, its implementation in communication networks has been relatively sparse, despite being considered of paramount importance. This workshop seeks to address this gap by shedding light on the potential applications of Trustworthy and Explainable AI in achieving transparent AI-based automation for networking. The primary objective of the workshop is to foster collaboration among AI/ML and telecom engineers, facilitating the sharing and exchange of experiences and ideas related to all aspects of trustworthy and explainable AI for network management. Topics of Interest The topics of interest for TX4Nets 2024 include, but are not limited to: * XAI for Model Trustworthiness in Networks * XAI for Trustworthy Network management * XAI-driven Network Performance Optimization * Trustworthiness in AI Models for Communication Networks * XAI for trustworthy AI in Optical, Wireless, Microwave, B5G/6G Networks * XAI for Optical, Wireless, or Microwave Networks * XAI for Autonomous Networks * XAI for Zero Touch Networks * XAI for the Edge/Cloud and Internet-of-Things * XAI for network security, privacy, resilience, reliability, and safety * XAI Applied to Networking * XAI Applied to Network Management * XAI applied to Failure Management * Security and Explainability in AI for Communication Networks * Reliability and Explainability in AI for Communication Networks * Human-in-the-Loop Systems for AI in Communication Networks * Fair Federated Learning for Communication Networks * Fair AI-based Resource Allocation in Communication Networks * Model Uncertainty Quantification and Explainability for Communication Networks * Model Uncertainty Quantification and Explainability for Network Security * Conformal Predictions Applied to Communication Networks * Impact of Adversarial Attacks on Communication Networks AI Model Trustworthiness * Case Studies and Deployments of XAI in Communication Networks * XAI for Open RAN in 6G Networks * AI for trustworthy IoT and Autonomous System Applications * Ethical Considerations in AI for Communication Networks * Interoperability and Standards in AI for Communication Networks * Regulatory Landscape for AI in Communication Networks * New Business Models for XAI * Explainable Reinforcement Learning in Communication Networks * Causal Machine Learning for Networking * Causal Reinforcement Learning for Networking * XAI for federated learning-based solutions of 5G/6G and future networks * XAI for transfer learning-based solutions of 5G/6G and future networks * XAI for digital twin-based solutions of 5G/6G and future networks Important Dates Paper Submission: April 14, 2024 (extended, firm) Notification of Acceptance: April 27, 2024 Camera-ready Submission: May 6, 2024 Workshop Date: 3 June 2024 (tentative) Paper Submission Authors are invited to submit original contributions that have not been published nor has been submitted for publication elsewhere. Papers should be prepared using the IEEE double-column conference style (10pt font) and are limited to 6 pages including references. Papers must be submitted electronically in PDF format on EDAS through this link: https://www.edas.info/newPaper.php?c=31469&track=123080 All papers will be peer reviewed and the comments will be provided to the authors. Once accepted, the paper will be included in the conference proceedings and will be eligible for submission to the IEEE Xplore Digital Library. At least one author of each accepted paper is required to register and present the work in the workshop. Further information can be found on the official website of TX4Nets 2024: https://sites.google.com/view/tx4nets2024 Workshop Organizers Omran Ayoub, University of Applied Sciences of Southern Switzerland, Switzerland Cristina Rottondi, Politecnico di Torino, Italy Tania Panayiotou, University of Cyprus, Cyprus Sebastian Troia, Politecnico di Milano, Italy Marco Savi, University of Milano-Bicocca, Italy

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PhD in Conformal Prediction and Credal Probabilistic Machine Learning
by Michele Caprio 08 Mar '24

08 Mar '24

Dear SIPTian, Are you a Master's student in ML, AI, Statistics, Engineering, or Applied Mathematics and you're interested in a new paradigm for Uncertainty Quantification? Are you an expert in Conformal Prediction and you want to explore its relationship with model-based approaches? Then consider applying to work with me on these topics <https://www.findaphd.com/phds/project/relationship-between-conformal-predic…> for your PhD! You'd be part of the UKRI AI Centre for Doctoral Training <https://ai-decisions-cdt.github.io/hugo-pages/#about> (CDT) in Decision Making for Complex Systems, a newly-established joint CDT between the University of Manchester and Cambridge University. Collaborations are possible and encouraged between students, supervisors <https://ai-decisions-cdt.github.io/hugo-pages/#people>, and members of the Manchester Centre for AI Fundamentals <https://www.idsai.manchester.ac.uk/research/centre-for-ai-fundamentals/>. You should apply through the official university's website <https://www.se.manchester.ac.uk/phds-science-engineering/?utm_source=course…> and create an account. You should then apply for the PhD Artificial Intelligence CDT program (see attached picture). When asked about "Research details", you can use the project details that you can find here <https://www.findaphd.com/phds/project/relationship-between-conformal-predic…>. You don't need to submit a new research proposal. I hope to hearing from you soon, Yours, Michele Caprio

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PhD @Idsia in Counterfactual Fairness and Causal Explainability
by Antonucci Alessandro 06 Mar '24

06 Mar '24

Ph.D. Position @Idsia in the area of Counterfactual Fairness and Causal Explainability Deadline: March 28, 2024 The Dalle Molle Institute for Artificial Intelligence (IDSIA, idsia.ch) of Lugano (Switzerland) has an open position for a PhD student. This is a full-time (100%) position for a student active in the area of Counterfactual Fairness and Causal Explainability. The PhD research focuses on the fairness, explainability, and robustness of machine learning systems within the framework of causal counterfactual analysis using formalisms from probabilistic graphical models, probabilistic circuits, and structural causal models. The successful candidate holds a Master’s degree in Engineering or another STEM field (obtained or close to being obtained). Experience with Pytorch and proficiency in Python are optional but desirable skills. The starting date is May 2024 (or as can be arranged by mutual agreement). For further information, please get in touch with Alessandro Antonucci (alessandro(a)idsia.ch) and Alessandro Facchini (alessandro.facchini(a)idsia.ch) The link for the application is https://www.supsi.ch/en/bando2008. Applications should be submitted by March 28th, 2024.

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IPMU 2024 last call ! (extended deadline: March 8th)
by Christophe Marsala 01 Mar '24

01 Mar '24

Dear Sir, Could you, please, forward this announcementof the next IPMU conference to your ISIPTA mailing list? I thank you in advance, Best regards, Christophe Marsala ------------------------------------------------------------- Due to several requests, and to let you enough time to prepare you submission, the deadline to submit papers is extended for the last time to *March 8th, 2024*. Don't miss the opportunity to attend IPMU in Lisboa ! Best regards, Christophe Marsala ----------------------------------------------- *20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 2024,* Lisbon, Portugal, July 22–26, 2024 https://ipmu2024.inesc-id.pt/ The IPMU conference is organized every two years with the focus of bringing together scientists working on methods for the management of uncertainty and aggregation. It also provides a forum for the exchange of ideas between theoreticians and practitioners in these and related areas. The 2024 edition of IPMU will take place at Instituto Superior Tecnico, University of Lisbon, Portugal, located in a vibrant renovated area 10 minutes from downtown. Lisbon is one of the oldest cities in the world, and full of stories to tell. A city where you feel safe wandering around day or night, where you'll find hotels, restaurants and nightlife to suit every taste, budget and requirement. A city full of authenticity, where old customs and ancient history intermix with cultural entertainment and hi-tech innovation. Lisbon is ageless, but it loves company, being famous for its hospitality and the family-like way it welcomes visitors. Lisbon has been elected World's Leading City Destination at the 2018 World Travel Awards. *Topics and Scope of the Conference **/Theory, Methods and Tools:/* Uncertainty, Computational Intelligence, Bayesian and Probabilistic Methods, Information Theory, Measures of Information and Uncertainty, Evidence and Possibility Theory, Utility Theory, Fuzzy Sets and Fuzzy Logic, Fuzzy Control, Rough Sets, Multiple Criteria Decision Methods, Aggregation Methods, Knowledge Representation, Approximate Reasoning, Non-classical Logics, Default Reasoning, Belief Revision, Argumentation, Ontologies, Uncertainty in Cognition, Graphical Models, Knowledge Acquisition, Interpretable Machine Learning, Evolutionary Computation, Neural Networks, Data Analysis/Data Science, Explainable AI. /*Application Fields: */Intelligent Systems and Information Processing, Decision Support, Database and Information Systems, Information Retrieval and Fusion, Speech and Natural Language Processing, Image Processing, Multi-Media, Agents, Pattern Recognition, Medicine and Bioinformatics, Finance, Software Engineering, Industrial Engineering, Big Data. /IPMU'2024 solicits original research contributions of theoretical and methodological nature as well as application-oriented work./ *IPMU'24 keynote speakers * * Judea Pearl (University of California, Los Angeles, USA) * Keeley Crocket (Manchester Metropolitan University, UK) * Mário Figueiredo (IT / Instituto Superior Técnico, Universidade de Lisboa, Portugal) * Ruth Byrne (Trinity College, Dublin, Ireland) * Thierry-Marie Guerra (Université Polytechnique Hauts-de-France, France) *IMPORTANT DATES* - Special session proposals: December 4th, 2023 - Notification of acceptance special sessions: December 11th, 2023 - Paper submission: *March 8th, 2024*/(last extension)/ - Notification of acceptance: April 5th, 2024 - Camera-ready paper submission: April 30th, 2024 - Early/author registration: April 30th, 2024 - Conference: July 22nd-26th, 2024 /General Chair /João Paulo Carvalho (Portugal)/ Program Chairs/ Marek Reformat (Canada) Marie-Jeanne Lesot (France) Susana Vieira (Portugal) /Publication Chair/ Fernando Batista (Portugal) /Special Session Chair:/ Anna Wilbik (Netherlands) /Publicity Chair/ Christophe Marsala (France) /Executive Directors/ Bernadette Bouchon-Meunier (France) Ronald R. Yager (USA) ----------------------------------------------

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Call for paper: SUM 2024 conference in Palermo (November 27-29)
by sdesterc 01 Mar '24

01 Mar '24

*** please disseminate this call to whomever may be interested. We apologise in case you received multiple copies *** =================================== Conference announcement + key dates =================================== The 15th International Conference on Scalable Uncertainty Management (SUM 2022) will be held in Palermo, Italy from November 27-29, 2024. See: https://sum2024.unipa.it/ Key dates (CET 23:59): Abstract Submission (optional but useful to organizers): June 17, 2024 Paper Submission: June 24, 2024 Notification: August 31, 2024 Camera-ready copies: September 15, 2024 Conference: Nov. 27-29, 2024 ============= Description ============= Established in 2007, the SUM conferences are annual events which aim to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as Artificial Intelligence and Machine Learning, Databases, Information Retrieval and Data Mining, the Semantic Web and Risk Analysis, and with the aim of fostering collaboration and cross-fertilization of ideas from the different communities. An originality of the SUM conferences is their care for dedicating a large space of their program to tutorials covering a wide range of topics related to uncertainty management. Each tutorial provides a survey of one of the research areas in the scope of the conference. ===================== Topics of Interest ===================== We solicit papers on the management of large amounts of complex kinds of uncertain, incomplete, or inconsistent information. We are particularly interested in papers that focus on bridging gaps, for instance between different communities, between numerical and symbolic approaches, or between theory and practice. Topics of interest include (but are not limited to): Imperfect information in databases - Methods for modeling, indexing, and querying uncertain databases - Top-k queries, skyline query processing, and ranking - Approximate, fuzzy query processing - Uncertainty in data integration and exchange - Uncertainty and imprecision in geographic information systems - Probabilistic databases and possibilistic databases? - Data provenance and trust - Data summarization - Very large datasets Imperfect information in information retrieval and semantic web applications - Approximate schema and ontology matching - Uncertainty in description logics and logic programming - Learning to rank, personalization, and user preferences - Probabilistic language models - Combining vector-space models with symbolic representations - Inductive reasoning for the semantic web Imperfect information in artificial intelligence - Statistical relational learning, graphical models, probabilistic inference Argumentation, defeasible reasoning, belief revision - Weighted logics for managing uncertainty - Reasoning with imprecise probability, Dempster-Shafer theory, possibility theory - Approximate reasoning, similarity-based reasoning, analogical reasoning - Planning under uncertainty, reasoning about actions, spatial and temporal reasoning - Incomplete preference specifications - Learning from data Risk analysis - Aleatory vs. epistemic uncertainty - Uncertainty elicitation methods - Uncertainty propagation methods - Decision analysis methods - Tools for synthesizing results ======================== Submission Guidelines ======================== SUM 2020 solicits original papers in the following three categories: - Long papers (at most 14 pages, references excluded): technical papers reporting original research or survey papers - Short papers (between 4 and 7 pages, references excluded): papers reporting promising work-in-progress, system descriptions, position papers on controversial issues, or survey papers providing a synthesis of some current research trends - Extended abstracts (2 pages) of recently published work in a relevant journal or top-tier conference All SUM submissions must be formatted according to the LNCS/LNAI guidelines:https://www.springer.com/gp/computer-science/lncs/conference-pro… Papers should be submitted via EasyChair: https://easychair.org/conferences/?conf=sum2024 ============= Publication ============= Accepted long (at most 14 pages) and short papers (2-7 pages) will be published by Springer in the Lecture Notes in Artificial Intelligence (LNAI) series. Authors of an accepted long or short paper will be expected to sign copyright release forms, and one author is expected to give a presentation at the conference. Authors of accepted abstracts (2 pages) will be expected to present their work during the conference, but the extended abstracts will not be published in the LNCS/LNAI proceedings (they will be made available in a separate booklet) ========================================================================================= Organization ========================================================================================= Sébastien Destercke (Université de technologie de Compiègne), PC Co Chair Maria Vanina Martinez (IIIA-CSIC), PC Co Chair Giuseppe Sanfilippo, (University of Palermo), General/Local Chair

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CFP: BELIEF 2024, Belfast, UK, Sept 4-6, 2024
by Thierry Denoeux 01 Mar '24

01 Mar '24

****** Call for Papers ****** https://bfasociety.org/Belief2024/ <https://antiphishing.vadesecure.com/v4?f=SnpNUUNxek1BTWh6ZFZjaXX1rV-mm6_xB2…> 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 ================================================================ Early Bird Registration Open Until: 22nd July 2024 Early Bird Registration: £325 (€380) Regular Registration: £375 (€440) Early Bird Student Registration: £225 (€265) Student Registration: £275 (€325) ================================================================ 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://www.bfasociety.org/ <https://antiphishing.vadesecure.com/v4?f=SnpNUUNxek1BTWh6ZFZjaXX1rV-mm6_xB2…>) 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.bi(a)ulster.ac.uk <mailto:y.bi@ulster.ac.uk>), Ulster University, UK Dr Anne-Laure Jousselme (anne-laure.jousselme(a)csgroup.eu <mailto:anne-laure.jousselme@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://www.hds.utc.fr/~tdenoeux

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On the necessity of causality
by Marco Zaffalon 26 Feb '24

26 Feb '24

Dear SIPTAnts, There’s this new paper that looks really cool and fundamental: https://arxiv.org/pdf/2402.10877.pdf. Loosely speaking, it shows that causal models are somewhat of a necessary consequence of being robust to a variety of conditions. Enjoy the read, Marco

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