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Thesis proposals in robust AI related fields
by sdesterc 07 Apr '23

07 Apr '23

Dear Colleagues, Our team is offering various PhD proposals, whose topics concern * Uncertainties and imprecision in Spatial Interpolations for Urban Risk Mapping: the PhD student would integrate the HOUSES national project, that aims at handling severe uncertainties in geostatistics, notably to assess pollutants levels in water and grounds. * Robustness in Explainable AI: the PhD student would join our junior professor chair and develop robust explanation methods for AI predictive models, as well as explanation methods for uncertain predictions. * Robust event detection: the PhD student would join the SAFE AI chaire and develop statistical learning method that would detect events with pre-specified statistical guarantees, notably by working on how to obtain calibrated predictions for such tasks. The first retained case studies would concern obstacle detection for aid-decision in partially or fully automated vehicles, a domain on which our laboratory has significant expertise. For each of these, we seek highly motivated students having a strong background in mathematics or computer science, with a focus on a topic connected to the PhD proposals (e.g., statistics, machine learning, …) Potentially interested candidates can find more details on the page https://www.hds.utc.fr/~sdesterc/dokuwiki/. Best regards Sébastien -- ==================================== Sebastien Destercke, Ph. D. CNRS researcher in computer science. Université de Technologie de Compiegne U.M.R. C.N.R.S. 7253 Heudiasyc Avenue de Landshut F-60205 Compiegne Cedex FRANCE Tel: +33 (0)3 44 23 79 85 Fax: +33 (0)3 44 23 44 77 ====================================

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are you interested in submitting a paper to the special issue on Decision Making and Optimization under Uncertainty? let us know ASAP
by Kreinovich, Vladik 05 Apr '23

05 Apr '23

Dear Friends, Based on several recommendations, the MDPI open-access journal Mathematics http://www.mdpi.com/journal/mathematics contacted us to edit a special issue on Decision Making and Optimization under Uncertainty. The plan is to welcome papers related to all kinds of uncertainty: probabilistic (in particular, related to imprecise probabilities), interval, fuzzy, etc. The planned deadline for submissions is November 1, 2023. For the journal to better plan this issue, the journals asks all editors of special issues to provide a tentative list of possible submissions, with tentative title and list of authors - including their affiliation and emails. If you are interested in submission, please let us know as soon as possible, by April 18, 2023. To help you make your decision, here are two important facts about the journal: * Latest impact factor for Mathematics is 2.592 * This open access journal, this means that authors have to pay publication fee if the paper is accepted. Yours Martine Ceberio, Christoph Lauter, and Vladik Kreinovich.

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ISIPTA 2023: Call for Posters (deadline 1 May)
by Enrique Miranda 03 Apr '23

03 Apr '23

** *Apologies if you receive multiple announcements* *** The Thirteenth International Symposium on Imprecise Probability: Theories and Applications (ISIPTA 2023) Oviedo, 11-14 July, 2023. In our call for papers we stated that there is “Uncertainty modelling beyond probability” and tried to convince you that ISIPTA 2023 is a good place for discussing such matters. The paper submission deadline has passed, but rest assured, you can still present your work at ISIPTA, because poster abstract submission is open. These poster abstracts are intended for discussing preliminary results and open questions, or for bringing published results to the attention of the ISIPTA audience. Each accepted poster abstract will be announced in a short plenary spotlight presentation, and the accompanying poster will be presented at length during one of the discussion sessions. Given the prominent role of poster presentations at ISIPTA, these sessions provide you with a genuine opportunity for presenting your work to the ISIPTA audience. The deadline for poster submission is May 1. You can submit at any time before that, though, and we will provide you with a decision within two weeks. Not convinced yet? Then perhaps the following features can persuade you. Basic info:ISIPTA 2023 will take place in hotel ACForum in Oviedo, from July 11 to July 14, 2023. Additional information is available on our website: https://isipta23.sipta.org/ Scope:The ISIPTA conferences are devoted to robustness and imprecision in uncertainty modelling, inference and decision making, focusing in particular on uncertainty frameworks that extend or replace the probabilistic one. Invited speakers:ISIPTA 2023 will feature keynote talks by Gert de Cooman (Ghent University, Belgium), Marta Kwiatkowska (University of Oxford, United Kingdom) and Michel Grabisch (Université Paris I- Panthéon Sorbonne). In addition, a homage to the late Professor Terrence Fine will take place. Concept: Each accepted contribution is presented anddiscussed, in two separate sessions. Presentations are short and always plenary. Detailed explanations and discussions will take place in a poster session. Registration: Registration is open. The deadline for early registration is May 20, while the extended registration deadline is June 15. The early registration fees are 450 for regular, 250 for students and 150 for accompanying people. Atmosphere: ISIPTA conferences are characterised by a friendly and cooperative style, a strong emphasis on in-depth discussion and openness to new ideas. We hope that you too will enjoy and contribute to this unique atmosphere. Awards:ISIPTA 2023 will hand out an IJAR Young Researcher Award (for excellent research in the area of imprecise probabilities) and several poster awards. The IJAR award is sponsored by the International Journal of Approximate Reasoning. The deadline for applying for the IJAR Young Researcher Award is May 20; the rules for application are available on our website. Anyone who presents a poster (either for a paper or poster abstract) is eligible for the poster prizes. In addition, Artificial Intelligence Journal is sponsoring 4 fellowships of 750 euros for PhD or master students. We look forward to receiving your contribution. The ISIPTA 2023 Steering Committee F. Cozman (University of Sao Paulo, Brazil) J. De Bock (Ghent University, Belgium) E. Miranda (University of Oviedo, Spain) I.Montes (University of Oviedo, Spain) E. Quaeghebeur (Technical University of Eindhoven, The Netherlands) B. Vantaggi (University La Sapienza of Rome, Italy) *

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Call for Papers: papers using imprecise probabilities are welcome at this series of conferences
by Kreinovich, Vladik 29 Mar '23

29 Mar '23

CALL FOR PAPERS The Seventh International Econometric Conference of Vietnam - ECONVN2024 Ho Chi Minh City, Vietnam, January 09-11, 2024 Main theme: PARTIAL IDENTIFICATION IN ECONOMETRICS AND RELATED TOPICS We have witnessed recent developments in the partial identification approach in econometrics since the early 1990s. Therefore, the Seventh International Econometric Conference of Vietnam (ECONVN2024) aims to address the latest ideas and developments in econometrics for economics and related topics, emphasising the benefits and challenges of using partially identified models in empirical research. Selected papers will be published in the Springer series "Studies in Systems, Decision, and Control" (Scopus, DBLP, WTI Frankfurt eG, zbMATH, SCImago) and will be submitted for consideration in Web of Science (ISI). Venue: Ho Chi Minh University of Banking (HUB), 36 Ton That Dam Street, District 1, Ho Chi Minh City, Vietnam Format: A Hybrid Conference with both Online and Offline Conference Date: January 9-11, 2024 Conference Website: hcm-hn.conference-econ-buh-bav-rist.vn Point of Contact: vietnam.buh.econvn(a)gmail.com<mailto:vietnam.buh.econvn@gmail.com> Tel: (84) 28.382.102.38 The Conference welcomes research contributions to all aspects of partial identification in econometrics, with special emphasis on, but not limited to different techniques: Partial identification Bayesian statistics and computation; Uncertainty formalisms; Modelling uncertainty and inconsistency in big data; Uncertainty modelling in machine learning and deep learning; Information fusion and knowledge; Aggregation operators; Copulas for dependence modelling; Information fusion and knowledge integration in uncertain environments; Etc. and their applications to economics and econometrics. Publications: Accepted papers must be presented at the Conference which will be published (a few months after the conference dates) in the Springer Volume, Series: STUDIES IN SYSTEMS, DECISION AND CONTROL (Economics, Social and Life Science Classifications) Indexed by SCOPUS, SCImago (submitted for Web of Science) Important Dates: ● Paper submission deadline: July 31, 2023. ● Notification of acceptance: October 1, 2023. ● Camera-Ready Manuscript: October 31, 2023. Instructions for Submissions: ● Get your account on EasyChair (then click on Conferences, on ECONVN2024) and submit your PDF files to EasyChair. Link: https://easychair.org/conferences/?conf=econvn2024 ● Make sure your PDF files have Authors' EMAILS on them for correspondence. Registration Fee 1. Presenters ● Presenter + publication USD 200 (non-residents)/VND 7,000,000 (residents) ● Student + publication USD 100 (non-residents)/VND 4,800,000 (residents) 2. Participants: ● General USD 100 (non-residents)/VND 2,300,000 (residents) ● Student USD 30 (non-residents)/VND 1,000,000 (residents) *Authors from Ho Chi Minh University of Banking (HUB) and Co-organizers are discounted by 50%. Plenary Invited Speakers Arnab Bhattacharjee (UK) Christian Bontemps (France) William Briggs (USA) Boualem Djehiche (Sweden) Daniel S. Hain (Denmark) Marc Hallin (Belgium) Toru Kitagawa (UK) Vladik Kreinovich (USA) Poom Kumam (Thailand) Hung T. Nguyen (USA & Thailand) Tonghui Wang (USA) Calla Wiemer (Philippines) Woraphon Yamaka (Thailand) General Chair Doan Thanh Ha (Chair) Nguyen Duc Trung (Co-chair) Nguyen Tran Phuc Ha Thi Thieu Dao Organizing Committee CHAIR: NGUYEN NGOC THACH Secretary: Diem Pham Thi Thuy Scientific Committee CHAIR: HUNG T. NGUYEN (USA & Thailand) Members: Akira Namatame (Japan) Arnab Bhattacharjee (UK) Bernadette Bouchon-Meunier (France) Boris Choy (Australia) Boualem Djehiche (Sweden) Calla Wiemer (Philippines) Cathy Chen (Taiwan) Christian Bontemps (France) Daniel S. Hain (Denmark) Daniel Schmidt (Australia) David Trafimov (USA) Duan Jin-Chuan (Singapore) Poom Kumam (Thailand) Galit Shmueli (Taiwan) Irina Perfilieva (Czech Republic) John Harding (USA) Katsuhiro Sugita (Japan) Marc Hallin (Belgium) Marc Paolella (Switzerland) Mark Schaffer (UK) Michael Eichter (Netherlands) Michael Wolf (Switzerland) Michio Sugeno (Japan) Nguyen Duc Trung (Vietnam) Nguyen Ngoc Thach (Vietnam) Niels Haldrup (Denmark) Paulo Fraga Martins Maio (Finland) Polina Khrennikova (UK) Poom Kumam (Thailand) Radim Jirousek (Czech Republic) Rakesh Gupta (Australia) Sa-At Nipong (Thailand) Tonghui Wang (USA) Vilem Novak (Czech Republic) Vladik Kreinovich (USA) Vyacheslav Yukalov (Russia) William Briggs (USA) Mark Schaffer (UK) Janusz Kacprzyk (Poland) Emmanuel Haven (Canada) Polina Khrennikova (UK) Toru Kitagawa (UK) Woraphon Yamaka (Thailand) Ying Chen (Singapore)

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PhD position in Deep Neural Networks with Dempster Shafer Theory
by Sébastien Ramel 28 Mar '23

28 Mar '23

Description PhD position in Deep Neural Networks with Dempster Shafer Theory (Fully funded) Place: LGI2A, Université d’Artois, Béthune, France Starting date: October 2023 Candidate before May 2023 Duration : 3 years Website: https://www.lgi2a.univ-artois.fr/spip/en/open_positions/open-position-25 Subject Deep neural networks (DNNs) refer to predictive models that exploit multiple layers of artificial neurons to compute a prediction [1,4]. In the original version, the layers are sequential and each neuron in a layer is connected with neurons in the previous layer. Many other alternative architectures have been proposed to adapt DNNs to solve specific and complex problems. On the other hand, a theory called Dempster-Shafer theory of belief functions, or theory of evidence [15], has emerged as a rich and flexible generalization of the Bayesian probability theory, able to deal with imperfect (uncertain, imprecise, …) information. It is notably used in a growing number of applications such as classification (e.g. [2]), clustering (e.g. [3,7]) or information fusion (e.g. [5,13]). Recent works [6,16,17] have shown the interest of enriching a DNN with an additional distance-based Dempster Shafer layer [2] for predicting belief functions. These belief functions can be of great interest to represent a reality as faithfully as possible, for example to perform a partial classification [8], i.e. decisions in favor of a group of classes. The main idea of this thesis is to develop such deep evidential networks in more depth by exploiting methods developed at LGI2A allowing one to consider finer knowledge about the quality [12, 14] and the dependence of information [11], or the ignorance in predictions [9,10]. Two applications are envisaged: Image analysis from drones and fish population analysis. To apply, please send the following documents grouped in one pdf file: your CV, your grades for the current and past years, a motivation letter, and at most two recommendations (optional) to sebastien.ramel(a)univ-artois.fr, frederic.pichon(a)univ-artois.fr and david.mercier(a)univ-artois.fr References [1] C. M. Bishop. Pattern recognition and machine learning, 5th Edition. Information science and statistics. Springer, 2007. [2] T. Denoeux. A neural network classifier based on dempster-shafer theory. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 30(2):131–150, 2000. [3] T. Denœux. Calibrated model-based evidential clustering using bootstrapping. Information Science, 528:17–45, 2020. [4] I. Goodfellow, Y. Bengio and A. Courville: Deep Learning (Adaptive Computation and Machine Learning), MIT Press, Cambridge (USA), 2016. [5] L. Huang, T. Denoeux, P. Vera, and S. Ruan. Evidence fusion with contextual discounting for multi-modality medical image segmentation. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 401–411. Springer, 2022. [6] L. Huang, S. Ruan, P. Decazes, and T. Denoeux. Lymphoma segmentation from 3D PET-CT images using a deep evidential network. International Journal of Approximate Reasoning, Volume 149, pages 39-60, 2022. [7] F. Li, S. Li, and T. Denœux. Combining clusterings in the belief function framework. Array, 6:100018, 2020. [8] L. Ma and T. Denœux. Partial classification in the belief function framework. Knowledge-Based Systems, 214: article 106742, 2021. [9] P. Minary, F. Pichon, D. Mercier, E. Lefèvre and B. Droit. Evidential joint calibration of binary SVM classifiers, Soft Computing, pp 4655-4671, Vol. 23, No. 13, 2019. [10] S. Ramel, F. Pichon and F. Delmotte. A reliable version of choquistic regression based on evidence theory, Knowledge-Based Systems, KBS, pp 106252, Vol. 205, 2020. [11] F. Pichon. Canonical decomposition of belief functions based on Teugels' representation of the multivariate Bernoulli distribution. Information Sciences, 428:76-104, 2018. [12] F. Pichon, D. Dubois, and T. Denœux. Relevance and truthfulness in information correction and fusion. International Journal Approximate Reasoning, 53(2):159–175, 2012. [13] F. Pichon, D. Dubois, and T. Denoeux. Quality of information sources in information fusion. In Éloi Bossé and Galina L. Rogova, editors, Information Quality in Information Fusion and Decision Making, pages 31–49. Springer, 2019. [14] F. Pichon, D. Mercier, E. Lefèvre, and F. Delmotte. Proposition and learning of some belief function contextual correction mechanisms. International Journal Approximate Reasoning, 72:4–42, 2016. [15] G. Shafer. A mathematical theory of evidence, volume 42. Princeton university press, 1976. [16] Z. Tong, P. Xu, and T. Denoeux. An evidential classifier based on dempster-shafer theory and deep learning. Neurocomputing, 450:275–293, 2021. [17] Z. Tong, P. Xu, and T. Denœux. Fusion of evidential cnn classifiers for image classification. In International Conference on Belief Functions, pages 168–176. Springer, 2021.

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Call for papers: GRID Workshop @ KR2023
by Sihem Belabbes 22 Mar '23

22 Mar '23

** Apologies for multiple postings ** CALL FOR PAPERS The First International Workshop on Graphical Reasoning with Imperfect Data, collocated with KR2023 (https://imsva91-ctp.trendmicro.com:443/wis/clicktime/v1/query?url=https%3a%…) Website: GRID2023 [1] INTRODUCTION The quality of real-world data is a major issue in many application domains, especially in data-intensive AI applications. As a matter of fact, the presence of inconsistent, incomplete, inaccurate or uncertain data may not only hamper problem modeling and solving, but also the process of explaining the solutions. More theoretical approaches, on the other hand, have provided graphical tools for principled knowledge representation and reasoning that are much more transparent than opaque real-world AI applications. Indeed, graphical models such as Bayesian networks, knowledge graphs and ontologies have long been used to facilitate the representation of and the reasoning with imperfect data. By providing a visual dimension, they contribute to increasing the understanding of the problem, and thus help practitioners, users (lay and expert) as well as engineers in designing solutions that improve trust, efficiency and transparency. The GRID workshop aims at bringing the applied and the theoretical approaches together for the benefit of both. Real-world applications can gain in explainability through the use of graphical models, while addressing the intrinsic challenges of poor quality data can improve the understanding and use of graphical models. Small workshops are often organised around one unifying theme, be it a methodological theme or a challenge. We here focus on both a methodological theme and a challenge. Our approach will bring together 1) a variety of methods drawing on graphical representation and 2) a variety of application domains dealing with different aspects of imperfect data. The varieties generate the necessary distance between approaches to provide opportunities for cross-pollination, while similarities of methods and domains make for a sufficient closeness guaranteeing mutual relevance. TOPICS This workshop welcomes submissions dealing with the general topics of graphical models and imperfect data and their integration, from the perspective of knowledge representation and reasoning. A non-exhaustive list of keywords includes: + Bayesian nets + Markov nets + Credal nets + Dung-style argumentation + Knowledge graphs + Ontologies + Data visualization tools + Inconsistent data + Uncertain data + Data integration + Multi-source data + Heterogeneous data + Consistency maintenance + Real-world data + Data imputation + Missing data + Spurious data + Data loss + Outliers + Adversarial data SUBMISSION GUIDELINES Papers should be formatted according to the LNCS style and submitted as a single PDF file. We welcome submissions of theoretical and practical work including early-stage research ideas, methods, tools and applications. We welcome short papers (2-6 pages), and long papers (up to 12 pages). All accepted papers will be considered for an oral presentation. The reviewing process will be light and driven more by relevance to the workshop and the paper's potential to foster discussion than by the technical maturity of the contribution. Workshop submissions and camera-ready versions will be handled by EasyChair. Please submit at: https://easychair.org/my/conference?conf=grid2023 IMPORTANT DATES - May 31, 2023: Submission deadline - July 4, 2023: Paper notification - July 31, 2023: Camera-ready papers due PROCEEDINGS The accepted papers will appear on the workshop website and the online proceedings will be non-archival. The copyright will remain with the authors. ORGANIZING COMMITTEE Sihem Belabbes, LIASD, IUT de Montreuil, Université Paris 8, France. Jürgen Landes, University of Milan, Italy. PROGRAM COMMITTEE Leila Amgoud (CNRS, Université Toulouse 3, FR), Martin Adamčík (Assumption University, TH), Paolo Baldi (University of Milan, IT), Sadok Ben Yahia (Tallinn University of Technology, EE), Salem Benferhat (Université d'Artois, FR), Meghyn Bienvenu, (CNRS, Université de Bordeaux, FR), Richard Booth (Cardiff University, UK), Camille Bourgaux (Ecole Normale Supérieure, FR), Katarina Britz (Stellenbosch University, SA), Giovanni Casini (ISTI-CNR, IT), Esther Anna Corsi (University of Milan, IT), Madalina Croitoru (Université de Montpellier, FR), Glauber De Bona (Universidade de São Paulo, BR), Francesco De Pretis (University of Modena and Reggio Emilia, IT), Andreas Herzig (CNRS, Université Toulouse 3, FR), Sa ̈ıd Jabbour (Université d'Artois, FR), Mardi Jankowitz (University of South Africa, SA), Souhila Kaci (Université de Montpellier, FR), Myriam Lamolle (Université Paris 8, FR), Marie-Jeanne Lesot (Sorbonne Université, FR), Quentin Manière (Universität Leipzig, DE), Nédra Mellouli (Université Paris 8, FR), Tommie Meyer (University of Cape Town, SA), Petrus Potgieter (University of South Africa, SA), Soroush Rafiee Rad (ILLC Universiteit van Amsterdam, NL), Adrien Revault d'Allonnes (Université Paris 8, FR), Kai Sauerwald (FernUniversität in Hagen, DE), Karima Sedki (Université Paris 13, FR), Tom Sterkenburg (Ludwig-Maximilians-Universität Munich, DE), Chris Swanepoel (University of South Africa, SA), Karim Tabia (Université d'Artois, FR), Matthias Thimm (FernUniversität in Hagen, DE), Ivan Varzinczak (Université Paris 8, FR), Srdjan Vesic (CNRS, Université d'Artois, FR). CONTACT belabbes@1 and juergen_landes@2 1: iut.univ-paris8.fr 2: yahoo.de Links: ------ [1] https://jlandes.wordpress.com/graphical-reasoning-with-imperfect-data-grid-…

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[CFP] 28th International Conference on Conceptual Structures (ICCS 2023) at the HU Berlin, Final Call (Deadline Extended)
by Kai Sauerwald 21 Mar '23

21 Mar '23

[Apologies for multiple postings.] ****************************************************************** Final Call for Papers: 28th International Conference on Conceptual Structures (ICCS 2023) September 11th-13rd, 2023, Berlin, Germany Website: https://iccs-conference.org/ Twitter: @iccs_confs Contact us: contact(a)iccs-conference.org ****************************************************************** ********** About ICCS ********** The International Conferences on Conceptual Structures (ICCS) focus on the formal analysis and representation of conceptual knowledge at the crossroads of artificial intelligence, human cognition, computational linguistics, and related areas of computer science and cognitive science. The ICCS conferences evolved from seven annual workshops on conceptual graphs, starting with an informal gathering hosted by John F. Sowa in 1986. Recently, graph-based knowledge representation and reasoning (KRR) paradigms have been getting more and more attention. With the rise of quasi-autonomous AI, graph-based representations provide a vehicle for making machine cognition explicit to human users. ICCS 2023 will take place in Berlin, Germany, in September 2023. Scholars, students and industry participants from different disciplines will meet for several weeks of conferences, workshops, summer schools, and public events to engage with the broad topics, issues and challenges related to knowledge in the 21st century. Submissions are invited on significant, original, and previously unpublished research on the formal analysis and representation of conceptual knowledge in artificial intelligence (AI). All papers will receive mindful and rigorous reviews that will provide authors with useful critical feedback. The aim of the ICCS 2023 conference is to build upon its long-standing expertise in graph-based KRR and focus on providing modelling, formal and application results of graph-based systems. In particular, the conference welcomes contributions that address graph-based representation and reasoning paradigms (e.g. Bayesian Networks (BNs), Semantic Networks (SNs), RDF(S), Conceptual Graphs (CGs), Formal Concept Analysis (FCA), CP-Nets, GAI-Nets, Graph Databases, Diagrams, Knowledge Graphs, Semantic Web, etc.) from a modelling, theoretical and application viewpoint. **************** Invited Speakers **************** The following speaker will give keynote talks in addition to the technical programme: - Camille Roth (French National Centre for Scientific Research, Centre Marc Bloch) - Henrik Müller (TU Dortmund University) - Nina Gierasimczuk (Technical University of Denmark) ****** Topics ****** - Topics include but are not limited to: - Existential and Conceptual Graphs - Graph-based models for human reasoning - Social network analysis - Formal Concept Analysis - Conceptual knowledge acquisition - Data and Text mining - Human and machine reasoning under inconsistency - Human and machine knowledge representation and uncertainty - Automated decision-making - Argumentation - Constraint satisfaction - Preferences - Contextual logic - Ontologies - Knowledge architecture and management - Semantic Web, Web of Data, Web 2.0, Linked (Open) Data - Conceptual structures in natural language processing and linguistics - Metaphoric, cultural or semiotic considerations - Resource allocation and agreement technologies - Philosophical, neural, and didactic investigations of conceptual, graphical representations ************************** Important Dates (Extended) ************************** - Abstract registration deadline: April 3, 2023 (AoE) - Submission deadline: April 10, 2023 (AoE) - Paper Reviews Sent to Authors: May 21, 2023 (AoE) - Rebuttals Due: May 28, 2023 (AoE) - Notification to authors: June 7, 2023 (AoE) - Camera-ready papers due: June 21, 2023 (AoE) ****************** Submission Details ****************** We invite scientific papers of up to fourteen pages, short contributions of up to eight pages, and extended poster abstracts of up to three pages. Papers and poster abstracts must be formatted according to Springer’s LNCS style guidelines and not exceed the page limit. Papers will be subject to double-blind peer review, in which the reviewers do not know the author's identity. We recommend using services like https://anonymous.4open.science/ to anonymously share code or data. Anonymized works that are available as preprints (e.g., on arXiv or SSRN) may be submitted without citing them. Submission should be made via EasyChair: https://easychair.org/conferences/?conf=iccs2023. All paper submissions will be refereed, and authors will have the opportunity to respond to reviewers’ comments during the rebuttal phase. Accepted papers will be included in the conference proceedings, published by Springer in the LNCS/LNAI series. Poster submissions will also be refereed, and selected poster abstracts might be included in the conference proceedings. At least one author of each accepted paper or poster must register for the conference and present the paper or poster there. Proceedings will be indexed by DBLP. ********** Organizers ********** General Chair: Robert Jäschke, Information Processing and Analytics, Humboldt University of Berlin, Germany Program Chairs: Manuel Ojeda Aciego, Dept. Applied Mathematics, University of Málaga, Spain Kai Sauerwald, Artificial Intelligence Group, FernUniversität in Hagen, Germany ***************** Program committee ***************** - Bernd Amann – Sorbonne Université – LIP6, France - Simon Andrews – Sheffield Hallam University, UK - L’ubomír Antoni – Univ. P.J. Safárik, Slovakia - Pierre Bisquert – INRAE, France - Tanya Braun – Univ. of Münster, Germany - Peggy Cellier – IRISA/INSA Rennes, France - Pablo Cordero — Univ. de Málaga, Spain - M.Eugenia Cornejo — Univ. de Cádiz, Spain - Diana Cristea – Babes-Bolyai Univ. Cluj-Napoca, Romania - Licong Cui – The Univ. of Texas Health Science Center at Houston, USA - Harry Delugach – Univ. of Alabama in Huntsville, USA - Dominik Endres – Univ. of Marburg, Germany - Jérôme Euzenat – INRIA, France - Marcel Gehrke – Univ. of Lübeck, Germany - Raji Ghawi – Technical Univ. of Munich, Germany - Ollivier Haemmerlé – IRIT, Univ. Toulouse le Mirail, France - Tom Hanika – Univ. of Kassel, Germany - Dmitry Ignatov – National Research Univ., Higher School of Economics, Russia - Hamamache Kheddouci – Univ. Claude Bernard, France - Petr Krajca – Univ. Palacky Olomouc, Czech Republic - Ondrej Krídlo — Univ. P.J. Safárik, Slovakia - Leonard Kwuida – Bern Univ. of Applied Sciences, Switzerland - Domingo López-Rodríguez — Univ. de Málaga, Spain - Philippe Martin – UEA2525 LIM, Univ. of La Réunion, France - Jesús Medina — Univ. de Cádiz, Spain - Amedeo Napoli – LORIA Nancy (CNRS – Inria – Univ. de Lorraine), France - Sergei Obiedkov – National Research Univ., Higher School of Economics, Russia - Carmen Peláez-Moreno – Univ. Carlos III Madrid, Spain - Heather D. Pfeiffer – Akamai Physics, Inc., USA - Uta Priss – Ostfalia University, Germany - Christian Sacarea – Babes-Bolyai Univ. Cluj-Napoca, Romania - Diana Sotropa – Babes-Bolyai Univ. Cluj-Napoca, Romania - Francisco Valverde-Albacete — Univ Rey Juan Carlos, Madrid, Spain *****************************************

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8th SIPTA seminar: Frank Riedel ("Knightian Uncertainty in Finance and Economics") 30th March
by sdesterc 16 Mar '23

16 Mar '23

Dear SIPTians and IP enthusiasts, We are delighted to announce our upcoming eight 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 eigth seminar will take place on the 30th of March (Thrusday). The zoom link for this seminar is https://utc-fr.zoom.us/j/83400465706 For this eigth seminar, we are very happy to have Frank Riedel as our speaker. Frank Riedel is, among other things, Professor for Mathematics and Economics at Bielefeld University, as well as Director of the Center for Mathematical Economics and Editor in Chief of Mathematics and Financial Economics. He has made many core contribution to the handling of uncertainty in Finance, in particular to deal with ambiguity and knighting uncertainty. On the 30th March, at 15:00 CET paris time (up to 17:00 CET, with a talk duration of 45min/1h), he will talk about "Knightian Uncertainty in Finance and Economics”. 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 30th March, at 15:00 CET, 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 now online at https://www.youtube.com/watch?v=4Xv-7P7J1og. See you at the seminar! Sébastien, Enrique and Jasper

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FW: IUKM 2023 Call for Papers
by Kreinovich, Vladik 12 Mar '23

12 Mar '23

FYI, imprecise probabilities are one of the highlighted topics. -----Original Message----- From: Van Nam Huynh <huynh(a)jaist.ac.jp> Dear All, The IUKM 2023 — The Tenth International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making is being held from November 02 — 04, 2023, in Kanazawa, Japan. Attached please find the call for papers and I appreciate your help in circulating it among your colleagues and students. Thanks a lot. Best wishes, Nam

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16th International Workshop on Constraint Programming and Decision Making CoProD'2023
by Kreinovich, Vladik 12 Mar '23

12 Mar '23

Typo corrected, my apologies FYI, papers related to imprecise probabilities are always welcome at this series of workshops ************************************************************ 16th International Workshop on Constraint Programming and Decision Making CoProD'2023 https://www.cs.utep.edu/interval-comp/coprod23.html May 30, 2023, Cincinnati, Ohio, USA. CoProD'2023 is the sixteenth edition of CoProD http://coprod.constraintsolving.com/. It will be held on May 30, 2023, right before the Annual Conference of the North American Fuzzy Information Processing Society NAFIPS'2023, Cincinnati, Ohio, USA, May 31 - June 2, 2023, https://nafips2023.com/ Constraint programming techniques are important components of intelligent systems. They constitute a declarative and efficient methodology to represent and solve many practical problems. They have been applied successfully to a number of fields, such as scheduling of air traffic, software engineering, networks security, chemistry, and biology. Despite the proved usefulness of these techniques, they are still under-utilized in real-life applications. One reason is the perceived lack of effective communication between constraint programming experts and domain practitioners about constraints, in general, and their use in decision making, in particular. Objectives of CoProD: * To present advances in constraint solving, optimization, and related topics; * To develop a network of researchers interested in constraint techniques, in particular researchers and practitioners that use numeric and symbolic approaches (or a combination of them) to solve constraint and optimization problems; * To address the gap between the great capacity of these techniques and their limited use. CoProD aims at encouraging presentation and discussion of on-going work. In particular, please note that there is room for presentation of ideas, as opposed to results only. It also aims at facilitating networking opportunities as well as cross-fertilization between the approaches used in the different attending communities. Therefore, besides active researchers in decision making and constraint programming techniques, we expect to have a wide attendance and participation of domain scientists -- whose input is highly valued in this workshop. Proceedings / Publication: Submissions are expected in the form of extended abstracts of at least 2 pages and ideally no more than 5 pages (a few more pages is OK), formatted using the Springer edited book format, style file svmult.cls and an example of using this file (not related to CoProD) are attached to the workshop website. Submissions have to be sent in pdf format AND LaTeX format to mceberio [at] utep [dot] edu and vladik [at] utep [dot] edu. A contact author should be specified in the submission email. The deadline for submissions is April 15, 2023 (Let us know if you need a few more days). Authors of accepted abstracts are expected to participate and present their work at the workshop. Participation / Submission: Participation is encouraged from people doing research in the area of decision making as well as from domain scientists. Submissions of ideas are also encouraged. Important dates: April 10, 2023: paper submission April 20, 2023: notification of acceptance May 1, 2023: camera-ready copy of abstracts due May 30, 2022: workshop Organizers: Martine Ceberio, the University of Texas at El Paso, mceberio(a)utep.edu<mailto:mceberio@utep.edu> Vladik Kreinovich, the University of Texas at El Paso, vladik(a)utep.edu<mailto:vladik@utep.edu> The previous editions of CoProD featured invited talks by highly recognized experts (listed in alphabetic order): * Purushotham Bangalore, CIS department, University of Alabama at Birmingham, USA * Martin Berz, Michigan State University, USA * Stefano Bistarelli, University of Perugia, Italy * Alessandro Dal Palu, University of Parma, Italy * Rina Dechter, Information and Computer Sciences, University of California Irvine, USA * Scott Ferson, Applied Bioinformatics, New York, USA * Juan Carlos Figueroa, Universidad Distrital de Bogota, Colombia * Patty Hough, Sandia National Lab, Livermore, California, USA * Luc Jaulin, Ecole Nationale Superieure des Techniques Avancees (ENSTA) Bretagne, France * Weldon Lodwick, University of Colorado Denver, Denver, Colorado, USA * Kyoko Makino, Michigan State University, USA * Francois Modave, Texas Tech Health Center, El Paso, Texas, USA * Tiago Oliveira, National Institute of Informatics (NII) in Tokyo, Japan. * Enrico Pontelli, New Mexico State University, Las Cruces, New Mexico, USA * James Raynolds, College of Nanoscale and Engineering, SUNY Albany, USA * Sigfried Rump, Hamburg University of Technology and Waseda University, Japan * Ken Satoh, National Institute of Informatics (NII) in Tokyo, Japan * Bart Selman, CS department, Cornell University, USA * Yaroslav D. Sergeyev, Università della Calabria, Italy * Sergey Shary, Novosibirsk State University, Russia * Young Jun Son, The University of Arizona, Tucson, USA * Xiaobai Sun, Duke University, USA * Alfredo Vaccaro, University of Sannio, Department of Engineering, Benevento, Italy * Leticia Velazquez, The University of Texas at El Paso, USA

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