[UAI] CFP: CANEW-2000 Workshop

From: lci@decsai.ugr.es
Date: Thu Jan 27 2000 - 08:49:13 PST

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    Dear colleagues,

    Please find enclosed the WEB page (which is under construction) for
    theCaNew'2000 Workshop.

       Bayesian and Causal Networks: from inference to data mining
                        August 21 or 22, 2000, Berlin, Germany

    A workshop held in conjunction with the

                                Fourteenth Biennial European Conference on
    Artificial Intelligence (ECAI 2000),

                                                               August
    20th-25th, 2000, Berlin, Germany

    Wep page: http://www.lsi.upc.es/~sanguesa/CaNew2000.html

    The workshop will focus on several topics on the area of Bayesian and
    Causal Networks. Special emphasis will be placed on the properties of
    networks related to inference, conditional independence, semantics, and
    equivalence condition for structures using alternative uncertainty
    calculi. In a similar vein, important topics will be on innovation
    learning methods, specially those integrating various forms of prior
    knowledge or departing from the traditional algorithms, i.e.,
    incremental methods or scalable algorithms (in the
    sense of being able to cope with large number of variables o big volumes
    of data). Applications are also welcome as well as methodological
    papers. Participants are encouraged to submit descriptions of work in
    progress on all areas. Selected papers will be published in a renowned
    journal after the workshop and following a second review phase.

    Topics:

        Properties and expressiveness of Bayesian and causal networks
            Conditional Independency relationships in networks
            New inference methods
            Relation to other formalisms for example:
                Causal theories
                Default Logics
            Expression in other formalisms uncertainty formalisms
                Possibilistic Networks

        Learning methods
            Identifying Causal Parameters
            Dependence-based methods
            Information-based methods
            Hybrid methods
            Learning in the presence of noise, hidden variables and
    incomplete data
            Comparative studies

        Practical applications
            Scaling up to large volumes of data
            Data Mining applications
            Applications to industry and services
            Applications in web mining and user modelling

    New or improved techniques or methods, as well as innovative
    applications are welcome. Presentations of the current state of ongoing
    research projects or applications, and contributions emphasizing
    integration of various technologies or paradigms are especially welcome.

    Important Dates

          February 21, 2000 - Deadline for submission of papers
          April 28, 2000 - Notification of acceptance/rejection
          June 2, 2000 - Final revised camera-ready copies
          August 21 or 22, 2000 - Workshop

    Workshop Committee

    Co-chairs

          Ulises Cort=E9s, Artificial Intelligence section, Technical
    University of Catalonia, Catalonia (ia@lsi.upc.es)
          Ramon Sang=FCesa, Artificial Intelligence section, Technical
    University of Catalonia, Catalonia (sanguesa@lsi.upc.es)

    Committee

          Lu=EDs M. de Campos, Departamento de Ciencias de la Computaci=F3n e=
     I.
    A., E.T.S. Ingenier=EDa Inform=E1tica, University of Granada, 18071 Grana=
    da
    (Spain) (lci@decsai.ugr.es)

          Hector Geffner, Sim=F3n Bol=EDvar University, Caracas, Venezuela.

          Serafin Moral. Departamento de Ciencias de la Computaci=F3n e I. A.=
    ,
    E.T.S. Ingenier=EDa Inform=E1tica, University of Granada, 18071 Granada
    (Spain) (smc@decsai.ugr.es)

          Juan F. Huete, Departamento de Ciencias de la Computaci=F3n e I. A.=
    ,
    E.T.S. Ingenier=EDa Inform=E1tica, University of Granada, 18071 Granada
    (Spain) (jhg@decsai.ugr.es)

          Arno Siebes, Centrum voor Wiskunde en Informatica CWI, Office:
    M349, Kruislaan 413 P.O. Box 94079, 1090 GB Amsterdam, The Netherlands
    (Arno.Siebes@cwi.nl)

          Marco Ramoni, Knowledge Media Institute, The Open University,
    Walton Hall, Milton Keynes , United Kindgdom MK7 6AA
    (M.Ramoni@open.ac.uk).

          Simon Parsons, Department of Electronic Engineering, Electronic
    Engineering Department, Queen Mary & Westfield College Mile End Road,
    London, 4NS (S.D.Parsons@elec.qmw.ac.uk).

    Address for Submissions and Further Information

    Proposals have to be submitted electronically (Word for Windows or Unix
    compatible postscript) to both co-chairs Ramon Sang=FCesa and Ulises
    Cort=E9s, at the following address:

    Ulises Cort=E9s / Ramon Sang=FCesa
    Artificial Intelligence section
    Dept. of Software
    Technical University of Catalonia
    Campus Nord - Edifici C5
    Jordi Girona 1-3
    E-08034 Barcelona
    Catalonia, Spain
    Voice: + 34 93 401 70 16 / + 34 93 401 73 34
    Fax: + 34 93 401 70 14
    e-mail: ia@lsi.upc.es, sanguesa@lsi.upc.es

    Further information on ECAI 2000 is available at the ECAI 2000 home
    page.

    The URL of this Workshop home page is
    http://www.lsi.upc.es/~sanguesa/CaNew2000.html



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