[agents] ICML 2012 - Last call for papers
Jingrui He
jingrui.he at gmail.com
Tue Feb 7 23:09:17 EST 2012
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The 29th International Conference on Machine Learning (ICML-2012)
June 26-July 1, 2012, University of Edinburgh, Scotland
Call for Papers
http://icml.cc/2012/
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ICML 2012 invites the submission of engaging papers on substantial,
original, and previously unpublished research in all aspects of
machine learning. We welcome submissions of innovative work on
systems that are self adaptive, systems that improve their own
performance, or systems that apply logical, statistical, probabilistic or
other formalisms to the analysis of data, to the learning of predictive
models, to cognition, or to interaction with the environment. We
welcome innovative applications, theoretical contributions, carefully
evaluated empirical studies, and we particularly welcome work that
combines all of these elements. We also encourage submissions that
bridge the gap between machine learning and other fields of research.
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IMPORTANT DATES:
Workshop and tutorial proposals due February 10, 2012
Paper submissions due February 24, 2012
Tutorials June 26, 2012
Main conference June 27-29, 2012
Workshops June 30-July 1,
2012
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Conference Format
The conference will include three days of technical presentations, one
day of tutorials, and two days of workshops. In addition, this year
the conference will co-located with the 25th Annual Conference on
Learning Theory (COLT 2012).
Accepted papers will each have an oral presentation as well as a
poster in an evening poster session. Awards will be given for papers
of outstanding quality. There will also be talks by several invited
speakers, and a banquet.
Paper Submission
The submission of papers and the management of the paper reviewing
process for the main conference will be entirely electronic.
Submissions will be accepted until Monday February 24, 23:59
Universal Time (3:59pm Pacific Standard Time). Detailed formatting
and submission instructions for authors are available on the
conference web site (http://icml.cc/2012/).
ICML 2012 will not accept any paper that is substantially similar to
another paper that is currently under review or has already been
accepted for publication in a journal or another conference. Please
clearly indicate in the submission which contributions are novel and
which are previous work, either by the authors or others. If a paper
submitted to ICML 2012 and another already published or already
submitted paper contain substantial overlap in content and this
overlap is not clearly indicated (anonymously) as being previous
work, then the ICML submission may be rejected on the grounds of
being a dual submission. Similarly, authors must withdraw their
papers if they submit an overlapping paper elsewhere during the
ICML review period. For papers published in substantially disjoint
communities (application conferences, for example), the amount of
novel content a paper needs to contain may be less, as long as the
submitted papers are themselves clearly targeted to a machine
-learning audience.
Reviewing Process
The review process this year incorporates several improvements.
Authors, reviewers, and area chairs indicate subject areas. With the
help of these subject areas, area chairs and reviewers bid for papers.
A first reviewer for each paper will be selected from those bids. New
this year, two area chairs will also be assigned to oversee reviewing
of each paper. Each area chair will manually appoint an additional
reviewer for each paper using input from the bids. Authors will have
the opportunity to see and respond to the reviews (and optionally
revise their paper) before a final decision is made. Final decisions
will be made using the input from all reviewers, the author feedback,
the area chairs, and the program chairs. Reviewing for ICML 2012
is double blind between authors and reviewers.
-The ICML 2012 Organizational Team
General Chair:
Andrew McCallum (University of Massachusetts Amherst)
Program Chairs:
John Langford (Yahoo! Research)
Joelle Pineau (McGill University)
Local Chair:
Charles Sutton (University of Edinburgh)
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