SIGKDD Special Issue on Negative Results

[Christophe Giraud-Carrier]

Dear all,

Maggie Dunham and I are co-editing a special issue of SIGKDD
Explorations entitled: "Data Mining Unexpected Results," where we will
collect papers presenting negative results and lessons learned from
using ML/DM.

As researchers, we often learn the most from negative results or
mistakes made in setting up experiments. Unfortunately, these learning
experiences do not usually make it into our published papers - until
now. As a leading researcher, we are sure that more novice colleagues
could learn a great deal by reading what you and other top researchers
have learned from unexpected results or experiments gone awry.

While this is not directly metalearning, it has some impact on it, as
part of our effort in metalearning is to gain insight into the
mechanisms of learning and where they apply (or not).

The special issue will consist of a combination of invited papers as
well as refereed papers submitted to an open CFP. Submitted papers are
to be rather short, 2-5 pages, and to the point, emphasizing what was
attempted, what was expected, what actually happened and what may be
learned from the unexpected result. The deadline for submission is
September 15th, 2010. The complete CFP is at:
http://dml.cs.byu.edu/~cgc/docs/SIGKDDExpl/CFP.html.

We hope that some of you will consider submitting a paper.
Cheers,
Christophe