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PhD Position at The University of Manchester in the area of Uncertainty in Machine Learning

by Michele Caprio

PhD Position at The University of Manchester in the area of Uncertainty in Machine Learning The UKRI AI CDT in Decision Making for Complex Systems<https://www.ai-decisions-cdt.ac.uk/> — joint between The University of Manchester and the University of Cambridge — has an open position for a PhD student in Manchester. The PhD research's more specific area is Imprecise Probabilistic Machine Learning. The research focuses on developing a new Multimodal Learning paradigm based on the notion of Credal Sets. This project allows for doing both fundamental and applied research, with the aim of advancing and bridging both theory and applications. The candidate should hold a master's degree in mathematics, computer science, statistics, or a related field. Further details about this position, and a link to the application system, can be found at https://www.findaphd.com/phds/project/multimodal-credal-learning-theory/?p1… For further information, please contact Michele Caprio (michele.caprio(a)manchester.ac.uk<mailto:michele.caprio@manchester.ac.uk>).

Nov. 7, 2024

First Announcement: 14th International Symposium on Imprecise Probabilities (ISIPTA 2025) - Bielefeld

by Alexander Erreygers

We are excited to announce that the 14th International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA 2025) will be held at the Bielefeld University Center for Interdisciplinary Research from Tuesday, July 15, 2025, to Friday, July 18, 2025. ISIPTA is the premier international event dedicated to the exploration of imprecise probabilities, providing a platform for both theoretical advancements and practical applications. We invite contributions on all aspects of imprecise probabilities, a term encompassing a wide range of mathematical and statistical models that quantify uncertainty without the restriction of precise probabilities. Topics of interest include, but are not limited to, sets of probability measures, partial preference orderings, game-theoretic probability, choice functions, interval probabilities, risk measures, nonlinear expectations, belief functions, and possibility theory. The symposium will feature both contributed sessions and keynote talks from leading experts in the field. Keynote speakers are • Carole Bernard (Grenoble École de Management & Vrije Universiteit Brussel) • Itzhak Gilboa (Hautes Études Commerciales de Paris) • Peter Grünwald (Centrum Wiskunde & Informatica & Leiden University) • Jan Obłój (University of Oxford) The deadline for full paper submissions is February 2nd, 2025. More information about submission will follow in due course. For further details, please visit the conference website: https://isipta25.sipta.org/home . We look forward to welcoming you to Bielefeld! The ISIPTA 2025 Steering Committee Jasper De Bock Sébastien Destercke Alexander Erreygers Max Nendel Frank Riedel Matthias Troffaes

Oct. 17, 2024

I: OASIS talk next Friday: Michele Caprio - Imprecise Probability in Machine Learning

by Michele Caprio

Of possible interest for someone in the SIPTA community 🙂 Yours, Michele ________________________________ Da: Paolo Perrone <paolo.perrone(a)cs.ox.ac.uk> Inviato: lunedì 14 ottobre 2024 10:08 A: talk-announce(a)cs.ox.ac.uk <talk-announce(a)cs.ox.ac.uk>; Rob Cornish <rob.cornish(a)stats.ox.ac.uk>; Kaushik Chintam <k.chintam(a)se23.qmul.ac.uk>; Michele Caprio <michele.caprio(a)manchester.ac.uk> Oggetto: OASIS talk next Friday: Michele Caprio - Imprecise Probability in Machine Learning Hi all, The OASIS seminar is back! (https://www.cs.ox.ac.uk/seminars/oasis/ [cs.ox.ac.uk]<https://urldefense.com/v3/__https://www.cs.ox.ac.uk/seminars/oasis/__;!!PDi…>) This Friday at 2 PM AM in Lecture Theatre A we are going to have an OASIS talk by Michele Caprio (University of Manchester), titled "Imprecise Probabilistic Machine Learning: Being Precise About Imprecision". The abstract is below. Before the talk some of us are planning to have lunch with the speaker. If you are interested in joining us, please let me know by Thursday morning. The talk is also accessible remotely, at the following Zoom link: https://cs-ox-ac-uk.zoom.us/j/99562853810?pwd=VmJFUlhNbVJwOUpjTE5hUk9LUkMvU… [cs-ox-ac-uk.zoom.us]<https://urldefense.com/v3/__https://cs-ox-ac-uk.zoom.us/j/99562853810?pwd=V…> Meeting ID: 995 6285 3810 Passcode: 983333 For further information see the following links, https://www.cs.ox.ac.uk/seminars/oasis/ [cs.ox.ac.uk]<https://urldefense.com/v3/__https://www.cs.ox.ac.uk/seminars/oasis/__;!!PDi…> https://www.cs.ox.ac.uk/seminars/2688.html [cs.ox.ac.uk]<https://urldefense.com/v3/__https://www.cs.ox.ac.uk/seminars/2653.html__;!!…> All the best, Paolo --- Speaker: Michele Caprio (University of Manchester) Title: Imprecise Probabilistic Machine Learning: Being Precise About Imprecision Abstract: This talk is divided into two parts. I will first introduce the field of “Imprecise Probabilistic Machine Learning”, from its inception to modern-day research and open problems, including motivations and clarifying examples. In the second part, I will present some recent results that I've derived on Imprecise Markov Processes. I will introduce the concept of an imprecise Markov semigroup Q. It is a tool that allows to represent ambiguity around both the initial and the transition probabilities of a Markov process via a compact collection of plausible Markov semigroups, each associated with a (different, plausible) Markov process. I will use techniques from geometry, functional analysis, and (high dimensional) probability to study the ergodic behavior of Q. I will show that, if the initial distribution of the Markov processes associated with the elements of Q is known and invariant, under some conditions that also involve the geometry of the state space, eventually the ambiguity around their transition probability fades. I call this property ergodicity of the imprecise Markov semigroup, and I will relate it to the classical notion of ergodicity. I will present ergodicity when the state space is Euclidean or a Riemannian manifold. The importance of my findings for the fields of machine learning and computer vision will also be discussed. This talk is based on the following work, https://arxiv.org/abs/2405.00081 [arxiv.org]<https://urldefense.com/v3/__https://arxiv.org/abs/2405.00081__;!!PDiH4ENfjr…>, where I also extend the results to the case where the state space is an arbitrary measurable space.

Oct. 16, 2024

Next SIPTA virtual seminar: Alessio benavoli on "Learning from preferences and choice functions", 24th October (3pm Paris time)

by sdesterc

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 24th of October (Thursday). The zoom link for this seminar is https://utc-fr.zoom.us/j/89110869537 For this new seminar, we are very happy to have Alessio Benavoli as our speaker. Alessio Benavoli is Associate Professor in Statistics at the School of Computer Science and Statistics, Trinity College Dublin, Ireland. Alessio is a widely recognised expert in imprecise probability theories, in which he has done foundational work, and has connected imprecise probabilities to a bunch of different fields such as Machine Learning, Artificial intelligence, Quantum Mechanics, Control, ... On the 24th of October, at 15:00 CEST:paris time (up to 17:00 CEST, with a talk duration of 45min/1h), he will talk about "Learning from preferences and choice functions”. 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. So please mark your calendars on the 24th of October, 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=2tGQi8tpVvY&list=PLXsgvF2_g5Ht-BYPWsSjcunA3… See you at the seminar! Sébastien, Enrique and Jasper

Oct. 14, 2024

FW: Call for Papers: IUKM 2025, 17 - 19 March 2025, Ho Chi Minh City, Vietnam (Extended deadline)

by Kreinovich, Vladik

FYI, imprecise probabilities are one of the highlighted topics -----Original Message----- From: Van Nam Huynh <huynh.vannam(a)gmail.com> Sent: Wednesday, October 2, 2024 9:09 AM Subject: Call for Papers: IUKM 2025, 17 - 19 March 2025, Ho Chi Minh City, Vietnam (Extended deadline) [Apologies for cross-posting. Your help in circulating this call for papers to potentially interested parties is highly appreciated.] ———————————————————————————————————————————————————— CALL FOR PAPERS ———————————————————————————————————————————————————— IUKM 2025: The Eleventh International Symposium on INTEGRATED UNCERTAINTY in KNOWLEDGE MODELLING and DECISION MAKING 17 - 19 March 2025, Ho Chi Minh City, Vietnam Conference website: https://www.jaist.ac.jp/IUKM/IUKM2025/ Submission deadline: 15 October, 2024 (Extended) ———————————————————————————————————————————————————— The International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM) aims to provide a forum for exchanges of research results, ideas for and experience of application among researchers and practitioners involved with all aspects of uncertainty management and application. The Eleventh International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2025) will be held in Ho Chi Minh City, Vietnam during 17-19 March, 2025, and be jointly organized by Industrial University of Ho Chi Minh City, University of Science (Vietnam National University Ho Chi Minh City), and Japan Advanced Institute of Science and Technology (JAIST). ———————————————————————————————————————————————————— Proposal for special sessions and workshops is encouraged and welcome. List of Topics: Relevant topics for the IUKM 2025 Symposium include (but are not limited to) the following: —————Theory and Methodology————— Uncertainty formalisms: Bayesian probability, Dempster-Shafer theory, imprecise probability, random sets, rough sets, fuzzy sets and interval methods Modelling uncertainty and inconsistency in big data Learning and reasoning with uncertainty Logics for reasoning under uncertainty Uncertainty modelling in machine learning and deep learning Information fusion and knowledge integration in uncertain environments Decision making under various types of uncertainty Aggregation operators for decision making Copulas for dependence modelling Granular and soft computing Computational intelligence —————Application————— Data mining and knowledge discovery Multi-agent reinforcement learning Ontology engineering and Semantic Web Privacy preserving data analysis Intelligent data analysis and modelling Agents and argumentation Natural language processing Medical informatics and bioinformatics Ranking and recommendation systems Big data and cloud computing Social network analysis and mining Sensor fusion System identification and modelling Diagnosis and reliability Decision support systems Kansei/affective engineering Service computing Engineering management Supply chain management Environmental management Economics and econometrics Statistics and Applications --------------------------------------------------- Paper Submission and Publication: The authors are invited to submit their full papers by 15 October, 2024. The submissions will be peer-reviewed for originality and scientific quality. As done in previous editions, the proceedings of IUKM 2025 will be published by Springer-Verlag in the Lecture Notes in Artificial Intelligence series, and be available at the Symposium. ————————————————————————— _______________________________________________ General Chairs: Masahiro Inuiguchi (Osaka University, Japan) Hieu T. Huynh (Industrial University of Ho Chi Minh City, Vietnam) Program Chairs: Van-Nam Huynh (Japan Advanced Institute of Science and Technology, Japan) Katsuhiro Honda (Osaka Prefecture University, Japan) Bac H. Le (University of Science, Vietnam National University (VNU)-Ho Chi Minh City, Vietnam)

Oct. 2, 2024

2024 SIPTA School: Lecture recordings/materials & recap

by Alexander Erreygers

Dear IP enthusiasts and sympathisers, It’s been more than a month already since the eleventh edition of the SIPTA School on Imprecise Probabilities took place in Ghent, so about time for us to announce that the recordings of (selected) lectures are available on SIPTA's YouTube channel<https://www.youtube.com/watch?v=gyDqpSY5B5s&list=PLXsgvF2_g5HsKtgnqhuW9sWQA…> and that all of the lecture material (slides, notebooks, …) is available on the school’s website<https://school24.sipta.org/programme>. If you want to get an even better idea of the nice atmosphere during the school, we encourage you to read Adrián Detavernier’s post on the SIPTA blog<https://sipta.org/blog/school-2024/> — although sometimes pictures<https://school24.sipta.org/photo-gallery/> do say more than words. Kind regards, Floris Persiau and Alexander Erreygers The 2024 SIPTA School organisers

Sept. 27, 2024

PhD Position at Eindhoven University of Technology (TU/e) in the area of Uncertainty in Artificial Intelligence

by Van Camp, Arthur

PhD Position at Eindhoven University of Technology (TU/e) in the area of Uncertainty in Artificial Intelligence The Uncertainty in Artificial Intelligence Group (https://uai.win.tue.nl<https://uai.win.tue.nl/>) at Eindhoven University of Technology has an open position for a PhD student. The employment is full time for five years, with an intermediate evaluation (go/no-go) after nine months. The PhD research's more specific area is imprecise probability theory. The research focuses on bringing the theory of choice functions to applications. This project allows for doing fundamental research, with the aim of advancing the theory towards applications. The candidate should hold a master's degree in mathematics, computer science, or a related field. Further details about this position, and a link to the application system, can be found at https://jobs.tue.nl/en/vacancy/phd-in-uncertainty-in-artificial-intelligenc…. For further information, please contact Arthur Van Camp (a.van.camp(a)tue.nl<mailto:a.van.camp@tue.nl>).

July 11, 2024

[CfP] Call for Contributions - WSCL @ ECAI 2024 Workshop - Deadline Extension

by Andrea Campagner

(Apologies for multiple postings) Call for Contributions Weakly Supervised and Cautious Learning (WSCL) workshop Bridging machine learning and uncertainty management Workshop Information Co-located with the 27th European Conference on Artificial Intelligence (ECAI 2024) Location: Santiago de Compostela, Spain Dates: 19-20th October 2024 Website: https://sites.google.com/unimib.it/wscl2024/ In recent years, machine learning (ML) has been increasingly applied in a variety of settings, with promise to analyze huge and heterogeneous volumes of data, improve decisional accuracy, and ease human labor. These systems have been predominantly built based on the supervised learning paradigm, which relies on the availability of huge amounts of data, assumed to be reliably labeled by human experts. However, with this increasing interest has also come the realization that the real-world is often far from the idealized perfection assumed in the supervised paradigm: data can be missing or noisy; supervision can be costly to obtain or have veracity issues; human users could fail at appropriating technologies based on ML, due to the incapability of ML models at reliably conveying their uncertainty. As a result, recently, increasing interest has been devoted to the development of techniques capable of dealing with these issues. These include uncertainty quantification and cautious learning, where the ML models convey to the users their uncertainty to improve reliability and reduce cognitive biases; as well as weakly supervised learning and its variants, such as incomplete supervision, where only a subset of training data is labeled; imprecise supervision, where the training data is coarse-grained labeled; and inaccurate supervision, where the labels are not always true. At the same time, due to the inherently multidisciplinary nature of these issues, there has been an increasingly deepened dialogue between ML and neighboring scientific fields, such as knowledge and uncertainty representation, as well as human-computer interaction, crowd-sourcing and active learning. The aim of this workshop is to explore how machine learning and related methods can handle weak supervision and provide more cautious and reliable support in the presence of data imperfection, as well as encourage broad discussion between ML researchers and experts in neighboring related fields whose underlying principles and foundations are central to allow the functioning of systems built on ML in less than perfect real-world settings. Topics of Interest We invite all researchers in AI and neighboring disciplines interested in the interplay between Machine Learning and Uncertainty to submit their work to WSCL workshop, which will be held during 19-20 October 2024, as a satellite event to the 27th European Conference on Artificial Intelligence (ECAI 2024). We welcome submissions on topics related to both weakly supervised learning and uncertainty quantification. More generally, the topics of interest include: ● Weakly supervised learning (including, learning from noisy data, multi-instance learning, learning from imprecise data, ...); ● Uncertainty quantification (including, probabilistic and Bayesian machine learning, conformal prediction, three-way decision, set-valued approaches, possibilistic and evidential machine learning, ...); ● Uncertainty management and non-standard theories of uncertainty (including, foundations of probability theory, rough sets, fuzzy sets and possibility theory, evidence theory and belief functions, imprecise probabilities and credal sets, ...); ● Conformal prediction and related methods (including, Venn prediction, online learning, compression models, algorithmic information theory); ● Human-AI interaction and uncertainty communication; ● Active learning; ● Crowd-sourcing and data perspectivism Submission Instructions We welcome different types of submissions: ● full original papers (up to 7 pages); ● extended abstracts (up to 4 pages); ● already published work; ● review transfer for papers rejected at ECAI main track. Each accepted submission, irrespective of the type, will be assigned an oral presentation slot. Articles rejected at the main track of the ECAI 2024 conference, but relevant to the topics of interest of the workshop, may be transferred at the WSCL workshop based on the ECAI reviews. If you want to take advantage of this option, aside from submitting your contribution to the workshop, you should also fill-in the form at https://forms.gle/QPav5rHVMCuSMhFZ9 before the 11th July 2024 Contributions should be submitted through the chairingtool platform, available at the following link: https://chairingtool.com/conferences/WSCL24/MainTrack/ Original submissions (both full papers and extended abstracts) should be formatted according to the ECAI formatting instructions, using the ECAI 2024 template and formatting requirements specified by ECAI. The purpose of workshop presentations is to get early feedback on new ideas and to stimulate discussions between researchers interested in weakly supervised and cautious learning. As such, there will be no formal proceedings, but we may post accepted papers on the workshop website for the benefit of the workshop participants if the authors agree to this (and the paper has not already been published). Also, depending on the number of accepted contributions we may decide on organizing a special issue on a relevant scientific journal. Key Dates ● Submission deadline: 12th July 2024 ● Review Transfer submission deadline: 12th July 2024 ● Accept/Reject communications: 18th July 2024 ● Early registration deadline: 15th August 2024 ● Workshop date: 19-20th October 2024 Organizers ● Andrea Campagner, IRCCS Ospedale Galeazzi Sant’Ambrogio (Milan, Italy), andrea.campagner(a)unimib.it (primary contact person) ● Davide Ciucci, University of Milano-Bicocca (Milan, Italy), davide.ciucci(a)unimib.it ● Sébastien Destercke, Heudyasic Laboratory, CNRS (Compiègne, France), sebastien.destercke(a)hds.utc.fr ●Luciano Sànchez, University of Oviedo(Oviedo,Spain), luciano(a)uniovi.es

July 1, 2024

IPMU2024 - Call for Participation

by Christophe Marsala

Dear All, The program of the IPMU 2024 conference is now online: https://ipmu2024.inesc-id.pt/?page_id=806 It is still time to register to attend the conference in Lisbon! 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 - 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) ----------------------------------------------

June 24, 2024

SUM 2024 - Call with EXTENDED DEADLINE (11 July)

by sdesterc

***Apologies if you receive multiple copies. Please disseminate to potentially interested colleagues.*** Dear colleagues, Due to various requests, we have decided to extend the SUM 2024 submission deadline to the 11 July. Please find below the main information regarding the conference. ========================================= Conference announcement + key dates ***EXTENDED*** ========================================= The 16th International Conference on Scalable Uncertainty Management (SUM 2024) 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 24, 2024 Paper Submission: July 11, 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 2024 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

June 21, 2024