[UAI] final CFP: International Conference on Machine Learning

From: Seth Rogers (rogers@rtna.daimlerchrysler.com)
Date: Sun Jan 16 2000 - 20:31:10 PST

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    [NOTE - The deadline extension that just appeared is a LATER posting -
    this one is older, got lost in my inbox - sorry. UAI moderator]

    A final reminder- only 12 days until the submission deadline.

                             Call for Papers

        THE SEVENTEENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING

                           June 29-July 2, 2000
                            Stanford University

    The Seventeenth International Conference on Machine Learning (ICML-2000)
    will be held at Stanford University from June 29 to July 2, 2000, in the
    heart of Silicon Valley. The conference will bring together researchers
    to exchange ideas and report recent progress in the computational study
    of learning.

    Topics for Submission

    ICML-2000 welcomes submissions on all facets of machine learning, but
    especially solicits papers on problem areas, research topics, learning
    paradigms, and approaches to evaluation that have been rare at recent
    conferences, including:

    - - the role of learning in natural language, vision and speech, planning
      and scheduling, design and configuration, logical and spatial reasoning,
      motor control, and more generally on learning for performance tasks
      carried out by intelligent agents;

    - - the discovery of scientific laws and taxonomies, the construction of
      componential and structural models, and learning at multiple levels
      of temporal and spatial resolution;

    - - the effect of the developers' decisions about problem formulation,
      representation, data quality, and reward function on the learning
      process;

    - - computational models of human learning, applications to real-world
      problems, exploratory research that describes novel learning tasks,
      work that integrates familiar methods to demonstrate new functionality,
      and agent architectures in which learning plays a central role;

    - - empirical studies that combine natural data (to show relevance) with
      synthetic data (to understand conditions on behavior), along with formal
      analyses that make contact with empirical results, especially where the
      aim is to identify sources of power, rather than to show one method is
      superior to others.
      
    Naturally, we also welcome submissions on traditional topics, ranging
    from induction over supervised data to learning from delayed rewards, but
    we hope the conference will also attract contributions on the issues above.

    Review Process

    The ICML-2000 review process will be structured to encourage publications
    covering a broad range of research and to foster increased participation
    in the conference. To this end, we have instituted:

    - - area chairs who will be responsible for recruiting papers in their area
      of expertise and overseeing the review process for those submissions;

    - - conditional acceptance of papers that are not publishable in their initial
      form, but that can be improved enough for inclusion in time to appear in
      the proceedings; and

    - - a review form that requires referees to explicitly list any problems
      with a paper, what it would take to overcome them, and, if they recommend
      rejection, why it cannot be fixed in time for inclusion.

    The overall goal is to make the review process more like that in journals,
    with time for the authors to incorporate feedback from reviewers. Each
    submitted paper will be reviewed by two members of the program committee,
    with the decision about its acceptance overseen by the responsible area
    chair and the program chair.

    Paper Submission

    Authors should submit papers using same format and length as the final
    proceedings version. The detailed instructions for authors at

       http://www-csli.stanford.edu/icml2k/instructions.html

    include pointers to templates for LaTeX and Word documents. These specify
    two-column style, Times Roman font with 10 point type, vertical spacing
    of 11 points, overall text width of 6.75 inches, length of 9.0 inches,
    0.25 inches between the two columns, top margin of 1.0 inch, and left
    margin of 0.75 inch. (The right and bottom margins will depend on whether
    one uses US letter or A4 paper.) Papers must not exceed eight (8) pages
    including figures and references. We will return to the authors any
    papers that do not satisfy these requirements.

    The deadline for submissions to ICML-2000 is MONDAY, JANUARY 24, 2000.
    Submission will be entirely electronic by transferring papers to the
    ICML-2000 ftp site, as explained in the detailed instructions for
    authors. Authors must submit papers in POSTSCRIPT format to ensure
    our ability to print them out for review.

    Each submission must be accompanied by the paper's title, the authors'
    names and physical addresses, a 250-word abstract, the contact author's
    email address and phone number, and the author who would present the
    talk at the conference. Authors must enter this information into the
    submission form at the conference web site by FRIDAY, JANUARY 21.

    ICML-2000 allows simultaneous submission to other conferences, provided
    this fact is clearly indicated on the submission form. Accepted papers
    will appear in the conference proceedings only if they are withdrawn
    from other conferences. Simultaneous submissions that are not clearly
    specified as such will be rejected.

    Other Conference Information

    The Seventeenth International Conference on Machine Learning will be
    collocated with the Thirteenth Annual Conference on Computational
    Learning Theory (COLT-2000) and the Sixteenth Conference on Uncertainty
    in Artificial Intelligence (UAI-2000). Registrants to any of these
    meetings will be able to attend the technical sessions of the others
    at no additional cost.

    ICML-2000 will also be preceded by tutorials on various facets of
    machine learning. For additional information, see the web site for
    the conference at

      http://www-csli.stanford.edu/icml2k/

    which will provide additional details as they become available. If
    you have questions about ICML-2000, please send electronic mail to
    icml2k@csli.stanford.edu.

    The conference has received support from DaimlerChrysler Research and
    Technology, Stanford's Center for the Study of Language and Information
    (CSLI), and the Institute for the Study of Learning and Expertise (ISLE).



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