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0123

Notice

AISB event Bulletin Item

CALL FOR PARTICIPATION: 2nd workshop on COmbining COnstraint solving with MIning and LEarning, July 1418, 2013, Washington, USA

http://4c.ucc.ie/cocomile/

(CoCoMiLe)- co-located with AAAI 2013

=====================
Overview:
=====================

The field of constraint solving has traditionally evolved quite independently from those of machine
 learning and data mining. In recent years, interest has been growing on the connections between 
these fields, and the potential advantages of their integration. Integration can work in two ways
 -- on one hand, various types of constraint solvers can be included in machine learning and data 
mining algorithms, for example to provide a uniform and effective way to characterize the desired 
solutions; on the other hand, machine learning can help in addressing constraint satisfaction 
problems, both at the level of search, by improving search or integrating intelligent 
meta-heuristics, as well as at the level of modelling, for example by learning constraints 
or interactively supporting a decision maker.

While promising initial results have been achieved in such directions, many options are unexplored 
and further research is needed in order to establish a systematic approach to this integration. 
The best way to reach the full potential of such integrations is in a multi-disciplinary way. 
This workshop is the second instalment after a successful start co-located with ECAI 2012.

The main purpose of this workshop is to provide an open environment where researchers in machine 
learning, data mining and constraint solving can exchange ideas and discuss on promising approaches,
crucial issues, open problems and interesting formalizations of new tasks. 
To encourage this, we will allow three different types of submissions: 1) original contributions 
(unpublished work), 2) relevant contributions recently submitted or published elsewhere (only oral)
and 3) vision statements, works in progress and short overviews.

The following is a non-exclusive list of possible topics:
- data mining/machine learning using constraint solving techniques
- learning with constraints
- constraint-based languages for data mining/machine learning
- preference learning for constraint solving
- automated constraint modeling and solving
- constraint acquisition
- interactive constraint solving
- solver portfolio optimisation
- machine learning in search
- integrating learning and search
- automated parameter optimization / algorithm configuration


In addition to the received contributions, the workshop will include invited talks from prominent 
researchers working in the intersection between constraint technology, machine learning and data 
mining. The workshop is planned to end with a broad discussion on the most relevant open problems 
and research directions.


=====================
Submission:
=====================
We accept the following three types of submissions (using AAAI format, see 
http://www.aaai.org/Publications/Templates/AuthorKit.zip):
Original novel and unpublished work (max. 6 pages);
An extended abstract of work-in-progress or position statements about future directions, 
possibilities and limitations (max. 2 pages);

Manuscripts that have recently been accepted for publication or appeared within the last 6 months 
in a peer-reviewed journal or which are currently under review (only oral, no page limit or format 
constraints)

Authors should take care that the submitted works are written at the level of the general AI 
audience, and not geared towards data mining or constraint solving expert specifically.

Submissions will be peer-reviewed by the program committee. All accepted submissions will be 
published as a AAAI technical report.


=====================
Important Dates:
=====================
3 April 2013: submission deadline (after notification for AAAI and IJCAI)
19 April 2013: acceptance notification
9 May 2013: camera-ready version due
14-15 July 2013: AAAI workshop program


=====================
Contacts:
=====================
Tias Guns 
Lars Kotthoff 
Barry O'Sullivan 
Andrea Passerini