IJCNN special session on Active Learning and Experimental Design

[Isabelle]

Active Learning and Experimental Design
Special Session at IJCNN 2013
http://perso.rd.francetelecom.fr/lemaire/IJCNN2013/

Fairmont Hotel • Dallas, TX
August 4–9, 2013
http://www.ijcnn2013.org/

organized within International Joint Conference on Neural Networks
sponsored jointly by INNS, the IEEE Computational Intelligence
Society.

This special session offers a meeting opportunity for academics and
industry researchers belonging to the communities of Computational
Intelligence, Machine Learning, Experimental Design, Causal Discovery,
and Data Mining to discuss new areas of active learning and
experimental design, and to bridge the gap between data acquisition or
experimentation and model building. The focus is on how active
sampling and data acquisition should contribute to the design and
modeling of highly intelligent learning systems.

Machine learning prescribes methods and algorithms, which allow a
model to learn a behavior from examples. Active learning gathers
methods, which select subsets of examples or variables to be used to
build a training set for the predictive model. Strategies must be
devised to select a subset of examples and variables as small and
informative as possible for a task at hand. As a special case, we
consider the problem of causal discovery in which one must uncover
variables susceptible of influencing a target of interest
quantitatively, due to a cause-effect relationship, and check such
hypothesis experimentally. Research on incremental experimental design
is particularly relevant to this call.

When designing active learning algorithms for real-world data, some
specific issues are raised. The main ones are scalability and
practicability. Methods must be able to handle high volumes of data,
in spaces of possibly high-dimension, and the process for labeling new
examples by an expert must be optimized. This includes making "de
novo" queries or equivalently for causal systems "manipulating" given
variables.

Publication opportunities: Papers should be submitted to IJCNN. We
encourage papers that describe applications of active learning in real-
world. In the industrial context, the main difficulties met and the
original solutions developed, have to be described. Authors of papers
accepted in the ECML-ALRA workshop (which do not have any "referenced"
proceedings) are also encouraged submit a long version of their paper
(up to the maximum number of pages at IJCNN). We are also planning a
special topic of JMLR on the theme of experimental design to uncover
causal relationships, which will be announced shortly.


Submission procedures: http://www.ijcnn2013.org/paper-submission.php#content
(Important - Submission Guidelines: Please follow the regular
submission guidelines of IJCNN 2013 and submit your paper to the paper
submission system. Be careful to select the correct special session.
After your submission notify the chairs of your submission by sending
email to:vincent...@orange.com.)

Further information:http://www.ijcnn2013.org

Important Dates:
Paper Submission Deadline February 22, 2013
Camera-Ready Paper Submission May 1, 2013

Organizers
• Vincent Lemaire (Orange Labs, France)
• José García-Rodríguez (University of Alicante, Spain)
• Isabelle Guyon (Clopinet Enterprises, USA)
• Alexis Bondu (EDF, France)


Contact
vincent...@orange.com, jga...@dtic.ua.es, gu...@clopinet.com,
alexis...@edf.fr