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[SIPTA] NMR'20 Deadlines: June 19 (abstract) and 26 (full paper) 2020
by Ivan José Varzinczak June 16, 2020

June 16, 2020

* Apologies if you receive multiple copies of this call * ============================== Call for Papers NMR 2020 Dates: 12-14 September 2020 Rhodes, Greece * Deadlines: 19 & 26 June 2020 * ============================== The 18th International Workshop on Nonmonotonic Reasoning (NMR) https://nmr2020.dc.uba.ar co-located with the International Conference on Principles of Knowledge Representation and Reasoning (KR) NMR is the premier forum for results in the area of nonmonotonic reasoning. Its aim is to bring together active researchers in this broad field within knowledge representation and reasoning (KRR), including belief revision, uncertain reasoning, reasoning about actions, planning, logic programming, preferences, argumentation, causality, and many other related topics including systems and applications. NMR has a long history - it started in 1984, and has been held every two years since then. Recent previous NMR workshops were held in Tempe (2018), Cape Town (2016), and Vienna (2014). NMR 2020 is co-located with KR 2020 and DL 2020. In particular, NMR 2020 will share a joint session with DL 2020. As in previous editions, NMR 2020 aims to foster connections between the different subareas of nonmonotonic reasoning and provide a forum for emerging topics. We especially invite papers on systems and applications, as well as position papers and papers addressing benchmark issues. The workshop will be structured by topical sessions fitting to the scopes of accepted papers. The workshop will be held in the Greek island of Rhodes, from 12 to 14 September 2020. Workshop activities will include invited talks and presentations of technical papers. -- Submission Information -- Papers should be at most 10 pages in AAAI style including references, figures, and appendices, if any. For further instructions on the format, please see the KR 2020 website. Papers must be submitted in PDF only. Please submit to: https://easychair.org/conferences/?conf=nmr2020 Papers already published or accepted for publication at other conferences are also welcome, provided that the original publication is mentioned in a footnote on the first page. In the same vein, papers under review for other conferences can be submitted with a similar indication on their front page. Papers that have already been published or submitted elsewhere may have over length. -- Workshop Proceedings -- There are no formal proceedings for NMR. The accepted papers will be published as a technical report and will be made available in the Computing Research Repository (CoRR). The papers will be compiled in the homepage of NMR 2020 (https://nmr2020.dc.uba.ar) The copyright of the papers lies with the authors, and as far as NMR is concerned, they are free to submit to other conferences and workshops as well. -- Important Dates -- - Paper registration deadline: 19 June 2020 - Paper submission deadline: 26 June 2020 - Notification to authors: 15 July 2020 - Camera ready version: 31 July 2020 - Workshop dates: 12-14 September 2020 -- Invited Speakers -- - Andreas Herzig, IRIT CNRS, France (joint session with DL 2020) - Francesca Toni, Imperial College London, UK -- Workshop Co-Chairs -- - María Vanina Martínez, Universidad de Buenos Aires and CONICET, Argentina - Ivan Varzinczak, CRIL, Univ. Artois & CNRS, France -- Program Committee -- - Ofer Arieli, Academic College of Tel-Aviv, Israel - Christoph Beierle, FernUniversitaet Hagen, Germany - Alexander Bochman, Holon Institute of Technology, Israel - Richard Booth, Cardiff University, UK - Arina Britz, Stellenbosch University, South Africa - Giovanni Casini, Université du Luxembourg - James Delgrande, Simon Fraser University, Canada - Juergen Dix, Clausthal University of Technology, Germany - Wolfgang Faber, Alpen-Adria-Universität Klagenfurt - Jorge Fandinno, IRIT-CNRS, France - Eduardo Fermé, Universidade da Madeira, Portugal - Martin Gebser, University of Potsdam, Germany - Laura Giordano, Universite of Piemonte Orientale, Italy - Lluis Godo Lacasa, IIIA - CSIC, Spain - Andreas Herzig, IRIT-CNRS, France - Aaron Hunter, British Columbia Institute of Technology, Canada - Anthony Hunter, University College London, UK - Katsumi Inoue, National Institute of Informatics, Japan - Tomi Janhunen, Aalto University, Finland - Souhila Kaci, Université Montpellier 2, France - Antonis Kakas, University of Cyprus - Gabriele Kern-Isberner, Technische Universitaet Dortmund, Germany - Sébastien Konieczny, CRIL-CNRS, France - Thomas Lukasiewicz, University of Oxford, UK - Thomas Meyer, University of Cape Town, South Africa - Nir Oren, University of Aberdeen, UK - Odile Papini, Aix-Marseille Université, France - Xavier Parent, Université du Luxembourg - Ramon Pino Perez, Universidad de Los Andes, Venezuela - Laurent Perrussel, Université de Toulouse, France - Ricardo O. Rodriguez, Universidad de Buenos Aires, Argentina - Ken Satoh, National Institute of Informatics and Sokendai, Japan - Gerardo Simari, Universidad Nacional del Sur and CONICET, Argentina - Guillermo R. Simari, Universidad del Sur in Bahia Blanca, Argentina - Christian Straßer, Ruhr-Universitaet Bochum, Germany - Matthias Thimm, Universität Koblenz-Landau, Germany - Leon van der Torre, Université du Luxembourg - Renata Wassermann, Universidade de São Paulo, Brazil - Emil Weydert, Université du Luxembourg - Stefan Woltran, Vienna University of Technology, Austria -- Further Information -- Please visit the workshop website (https://nmr2020.dc.uba.ar) for further information and regular updates. -- Ivan Varzinczak - https://www.ijv.ovh CRIL, Université d'Artois & CNRS, France

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[SIPTA] SLSP 2020: call for posters
by IRDTA June 15, 2020

June 15, 2020

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[SIPTA] IPMU'2020, IPMU"2022, and IPMU'2024 Information Processing and Management of Uncertainty in Knowledge-Based Systems
by Kreinovich June 15, 2020

June 15, 2020

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Re: [SIPTA] Kind Reminder：Call for Abstracts for the ICOSSAR2021, June 21-25, 2021, Shanghai, China
by Kreinovich June 14, 2020

June 14, 2020

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[SIPTA] [CFP] Extended deadline (26/6): uncertainty in machine learning workshop (WUML) at ECML/PKDD
by Sébastien Destercke June 11, 2020

June 11, 2020

---------------------------------------------------------- C A L L F O R P A P E R S (extended deadline: 26th June) Uncertainty in Machine Learning Workshop (combined with a tutorial) at ECML/PKDD 2020 September 18, 2020, Ghent, Belgium https://sites.google.com/view/wuml-2020/ ---------------------------------------------------------- Motivation and Focus ---------------------------------------------------------- The notion of uncertainty is of major importance in machine learning and constitutes a key element of modern machine learning methodology. In recent years, it has gained in importance due to the increasing relevance of machine learning for practical applications, many of which are coming with safety requirements. In this regard, new problems and challenges have been identified by machine learning scholars, which call for new methodological developments. Indeed, while uncertainty has long been perceived as almost synonymous with standard probability and probabilistic predictions, recent research has gone beyond traditional approaches and also leverages more general formalisms and uncertainty calculi. For example, a distinction between different sources and types of uncertainty, such as aleatoric and epistemic uncertainty, turns out to be useful in many machine learning applications. The workshop will pay specific attention to recent developments of this kind. This workshop will be preceded by a tutorial, which provides an introduction to the topic of uncertainty in machine learning and gives an overview of existing methods and hitherto approaches to dealing with uncertainty. ---------------------------------------------------------- Aim and Scope ---------------------------------------------------------- The goal of this workshop is to bring together researchers interested in the topic of uncertainty in machine learning. It is meant to provide a forum for the discussion of the most recent developments in the modeling, processing, and quantification of uncertainty in machine learning problems, and the exploration of new research directions in this field. We welcome papers on all facets of uncertainty in machine learning. We solicit original work, which can be theoretical, practical, or applied, and also encourage the submission of work in progress as well as position papers or critical notes. The scope of the workshop covers, but is not limited to, the following topics: -- adversarial examples -- belief functions -- calibration -- classification with reject option -- conformal prediction -- credal classifiers -- deep learning and neural networks -- ensemble methods -- epistemic uncertainty -- imprecise probability -- likelihood and fiducial inference -- model selection and misspecification -- multi-armed bandits -- online learning -- noisy data and outliers -- out-of-sample prediction -- performance evaluation -- hypothesis testing -- probabilistic methods -- Bayesian machine learning -- reliable prediction -- set-valued prediction -- uncertainty quantification ---------------------------------------------------------- Submission and Review Process ---------------------------------------------------------- Authors are supposed to submit original work in the form of regular and short papers written in English. The length of the papers is limited to 6 pages for short contributions (reporting work in progress) and 12 pages for regular contributions (reporting on more mature work) in LNCS format. All papers must be submitted in PDF format online via the EasyChair submission interface: https://easychair.org/conferences/?conf=wuml2020 Each submission will be evaluated by at least two members of the programme committee on the basis of its relevance to the workshop, the significance and technical quality of the contribution, and the quality of presentation. All accepted papers will be included in the workshop proceedings and will be publicly available on the conference web site (unless authors opt out). Currently, possibilities for a follow-up publication are also explored, for example a special issue in a journal. At least one author of each accepted paper is required to attend the workshop to present. ---------------------------------------------------------- Current Invited Speakers: ---------------------------------------------------------- * Meelis Kull, University of Tartu, Associate Professor in Machine Learning and Chair of Data Science ---------------------------------------------------------- Important Dates: ---------------------------------------------------------- 26th June 2020 --- paper submission 24th July 2020 --- notification of acceptance or rejection 30th July 2020 --- camera-ready version 18th September --- workshop date ---------------------------------------------------------- Organization: ---------------------------------------------------------- Eyke Hüllermeier, Paderborn University, eyke(a)upb.de Sébastien Destercke, Heudiasyc, Compiegne, sebastien.destercke(a)hds.utc.fr ---------------------------------------------------------- Programme Committee: ---------------------------------------------------------- * Viktor Bengs, Paderborn University * Hendrik Boström, KTH Royal Institute of Technology, Sweden * Giorgio Corani, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale * Ines Couso, University of Oviedo * Cassio de Campos, Eindhoven University * Juan J, Del Coz, University of Oviedo * Thierry Denoeux, University of Technology of Compiègne * Stefan Depeweg, Siemens * Peter Flach, Bristol University * Hanno Gottschalk, University of Wuppertal * Ulf Johansson, Jönköping University * Meelis Kull, University of Tartu * Benjamin Quost, University of Technology of Compiègne * Steffen Udluft, Siemens * Vladimir Vovk, Royal Holloway, University of London * Willem Waegeman, Ghent University * Marco Zaffalon, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale

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[SIPTA] BigDat 2020 Autumn: early registration June 26
by IRDTA June 9, 2020

June 9, 2020

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[SIPTA] IFSA/EUSFLAT'2021: mark your calendars
by Kreinovich June 8, 2020

June 8, 2020

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[SIPTA] [Online Conference]{3rd batch CFP} -9th International Conference on Data Mining & Knowledge Management Process (CDKP 2020)
by s kareem June 8, 2020

June 8, 2020

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[SIPTA] CfP: Workshop on “Explainable Logic-Based Knowledge Representation” (XLoKR 2020) in conjunction with KR 2020
by Francesco Kriegel June 8, 2020

June 8, 2020

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[SIPTA] CFP Workshop on Uncertainty in Machine Learning at ECML/PKDD 2020
by Sébastien Destercke June 4, 2020

June 4, 2020

---------------------------------------------------------- C A L L F O R P A P E R S Uncertainty in Machine Learning Workshop (combined with a tutorial) at ECML/PKDD 2020 September 14–18, 2020, Ghent, Belgium https://sites.google.com/view/wuml-2020/ ---------------------------------------------------------- Motivation and Focus ---------------------------------------------------------- The notion of uncertainty is of major importance in machine learning and constitutes a key element of modern machine learning methodology. In recent years, it has gained in importance due to the increasing relevance of machine learning for practical applications, many of which are coming with safety requirements. In this regard, new problems and challenges have been identified by machine learning scholars, which call for new methodological developments. Indeed, while uncertainty has long been perceived as almost synonymous with standard probability and probabilistic predictions, recent research has gone beyond traditional approaches and also leverages more general formalisms and uncertainty calculi. For example, a distinction between different sources and types of uncertainty, such as aleatoric and epistemic uncertainty, turns out to be useful in many machine learning applications. The workshop will pay specific attention to recent developments of this kind. This workshop will be preceded by a tutorial, which provides an introduction to the topic of uncertainty in machine learning and gives an overview of existing methods and hitherto approaches to dealing with uncertainty. ---------------------------------------------------------- Aim and Scope ---------------------------------------------------------- The goal of this workshop is to bring together researchers interested in the topic of uncertainty in machine learning. It is meant to provide a forum for the discussion of the most recent developments in the modeling, processing, and quantification of uncertainty in machine learning problems, and the exploration of new research directions in this field. We welcome papers on all facets of uncertainty in machine learning. We solicit original work, which can be theoretical, practical, or applied, and also encourage the submission of work in progress as well as position papers or critical notes. The scope of the workshop covers, but is not limited to, the following topics: -- adversarial examples -- belief functions -- calibration -- classification with reject option -- conformal prediction -- credal classifiers -- deep learning and neural networks -- ensemble methods -- epistemic uncertainty -- imprecise probability -- likelihood and fiducial inference -- model selection and misspecification -- multi-armed bandits -- online learning -- noisy data and outliers -- out-of-sample prediction -- performance evaluation -- hypothesis testing -- probabilistic methods -- Bayesian machine learning -- reliable prediction -- set-valued prediction -- uncertainty quantification ---------------------------------------------------------- Submission and Review Process ---------------------------------------------------------- Authors are supposed to submit original work in the form of regular and short papers written in English. The length of the papers is limited to 6 pages for short contributions (reporting work in progress) and 12 pages for regular contributions (reporting on more mature work) in LNCS format. All papers must be submitted in PDF format online via the EasyChair submission interface: https://easychair.org/conferences/?conf=wuml2020 Each submission will be evaluated by at least two members of the programme committee on the basis of its relevance to the workshop, the significance and technical quality of the contribution, and the quality of presentation. All accepted papers will be included in the workshop proceedings and will be publicly available on the conference web site (unless authors opt out). Currently, possibilities for a follow-up publication are also explored, for example a special issue in a journal. At least one author of each accepted paper is required to attend the workshop to present. ---------------------------------------------------------- Invited Speakers: ---------------------------------------------------------- * Meelis Kull, University of Tartu, Associate Professor in Machine Learning and Chair of Data Science More T.B.A. ---------------------------------------------------------- Important Dates: ---------------------------------------------------------- 11 June 2020 --- paper submission 20 July 2020 --- notification of acceptance or rejection 27 July 2020 --- camera-ready version 14th or 18th September --- workshop date ---------------------------------------------------------- Organization: ---------------------------------------------------------- Eyke Hüllermeier, Paderborn University, eyke(a)upb.de Sébastien Destercke, Heudiasyc, Compiegne, sebastien.destercke(a)hds.utc.fr ---------------------------------------------------------- Programme Committee: ---------------------------------------------------------- * Viktor Bengs, Paderborn University * Hendrik Boström, KTH Royal Institute of Technology, Sweden * Giorgio Corani, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale * Ines Couso, University of Oviedo * Cassio de Campos, Eindhoven University * Juan J, Del Coz, University of Oviedo * Thierry Denoeux, University of Technology of Compiègne * Stefan Depeweg, Siemens * Peter Flach, Bristol University * Hanno Gottschalk, University of Wuppertal * Ulf Johansson, Jönköping University * Meelis Kull, University of Tartu * Benjamin Quost, University of Technology of Compiègne * Steffen Udluft, Siemens * Vladimir Vovk, Royal Holloway, University of London * Willem Waegeman, Ghent University * Marco Zaffalon, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale

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