Connectionists: FINAL CFP: NIPS 2009 Workshop - Advances in Ranking

[Shivani Agarwal]

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                          FINAL CALL FOR PAPERS

                      ---- Advances in Ranking ----

                             Workshop at the
     23rd Annual Conference on Neural Information Processing Systems
                               (NIPS 2009)

             http://web.mit.edu/shivani/www/Ranking-NIPS-09/

               -- Submission Deadline: October 23, 2009 --

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                   [ Apologies for multiple postings ]

OVERVIEW
--------

Ranking problems are increasingly recognized as a new class of
statistical learning problems that are distinct from the classical
learning problems of classification and regression. Such problems arise
in a wide variety of domains: in information retrieval, one wants to
rank documents according to relevance to a query; in natural language
processing, one wants to rank alternative parses or translations of a
sentence; in collaborative filtering, one wants to rank items according
to a user's likes and dislikes; in computational biology, one wants to
rank genes according to relevance to a disease. Consequently, there has
been much interest in ranking in recent years, with a variety of methods
being developed and a whole host of new applications being discovered.

This workshop aims to bring together researchers interested in the area
to share their perspectives, identify persisting challenges as well as
opportunities for meaningful dialogue and collaboration, and to discuss
possible directions for further advances and applications in the future.

One of the primary goals of the workshop will be to reach out to a broad
audience. To this end, we will have talks on topics ranging from more
statistically/mathematically oriented approaches to ranking, to newer
application areas. A second goal will be to bring to the fore a range of
questions that are currently being debated within the community, for
example via a panel discussion between experts in the field.

Overall, the workshop will aim to provide a forum that showcases recent
advances in ranking to the broader community, facilitates open debate on
some of the questions in this area, and helps catalyze further interest
among those new to the topic.

FORMAT
------

This is a one-day workshop that will follow the 23rd Annual Conference
on Neural Information Processing Systems (NIPS 2009). The workshop will
consist of two 3-hour sessions. There will be 2-4 invited talks by
experts in the area, and 5-8 short talks. Depending on interest and
submissions, we may also have a short poster/demo session. There will be
time at the end of each talk/session for questions and discussion. We
also intend to have a panel discussion that will be moderated by the
organizers and that will bring together leading figures from both
academia and industry for discussion and debate.

Keynote Lecture
---------------

   * Persi Diaconis, Stanford University

Invited Talks
-------------

   * Ralf Herbrich, Microsoft Research Cambridge
   * Lek-Heng Lim, University of California, Berkeley

Contributed Talks
-----------------

These will be based on submissions of short papers. See below for
details.

CALL FOR PAPERS
---------------

We invite submissions of short papers addressing all aspects of ranking
in machine learning, data mining, and statistics, as well as related 
application areas. These include for example:

   * algorithms for ranking
   * mathematical/statistical analyses of ranking
   * relationships between ranking and other problems
   * applications of ranking in information retrieval, natural language
     processing, collaborative filtering, computational biology, computer
     vision, and other areas
   * benchmark data sets for ranking
   * challenges in applying or analyzing ranking methods

We also welcome papers on ranking that do not fit into one of the above
categories, as well as papers that describe work in progress.

Please note that papers that have previously appeared (or have been
accepted for publication) in a journal or at a conference or workshop,
or that are being submitted to another workshop, are not appropriate for
this workshop.

All papers presented at the workshop will be made available as
electronic proceedings. A print version will be distributed at the
workshop.

Submission Instructions
-----------------------

Submissions should be upto 4 pages in length using NIPS style files
(available at
http://web.mit.edu/shivani/www/Ranking-NIPS-09/StyleFiles/), and should
include the title, authors' names, postal and email addresses, and a
brief abstract. Email submissions (in pdf or ps format only) to
shivani at mit.edu with subject line "Workshop Paper Submission".

The deadline for submissions is Friday October 23, 5:00 pm EDT.
Submissions will be reviewed by the program committee and authors will
be notified of acceptance/rejection decisions by Wednesday November 11.
Final versions of accepted papers will be due on Wednesday November 18.

Please note that one author of each accepted paper must be available to
present the paper at the workshop.

RELATED WORKSHOP
----------------

There is a related workshop at NIPS this year titled Learning with
Orderings, with a somewhat different focus than ours; see the webpage
above for details. We encourage all participants of our workshop to
attend this workshop as well. Submissions should be directed to only one 
workshop; if a submission cannot be accommodated by one workshop, it may be 
forwarded to the other workshop for consideration. Please indicate if
you would like us to consider this.

IMPORTANT DATES
---------------

    First call for papers       --  September 15, 2009
    Paper submission deadline   --  October   23, 2009 (5:00 pm EDT)
    Notification of decisions   --  November  11, 2009
    Final papers due            --  November  18, 2009
    Workshop                    --  December  11, 2009

ORGANIZERS
----------

   * Shivani Agarwal, MIT
   * Chris J.C. Burges, Microsoft Research
   * Koby Crammer, The Technion

CONTACT
-------

Please direct any questions to shivani at mit.edu.

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