Call for papers: ICML-2k

[Sebastian Thrun]

Please find enclosed the CFP for ICML-2000.

It might interest you that ICML seeks to broaden its scope, and among other
areas solicits submissions from the connectionists/statistical learning
community. Consider submitting! It's a fun conference.


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                         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 at 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).