IJCAI 2015 Machine Learning Track - CALL FOR PAPERS

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IJCAI 2015 Publicity Chairs

Dec 30, 2014, 1:09:04 PM12/30/14
to IJCAI 2015 Publicity Chairs
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Machine Learning Track


24th International Joint Conference on Artificial Intelligence (IJCAI-15)

Machine Learning Track

Buenos Aires, Argentina / 25 July-1 August 2015


The Machine Learning Track Program Committee of the Twenty-fourth
International Joint Conference on Artificial Intelligence (IJCAI-15)
invites the submission of original technical papers to the Machine
Learning Track of IJCAI-15. Machine Learning is a core area of
artificial intelligence research, with implications and deep
connections to computer perception, automated cognition and
intelligent behavior. As a foundational subject, machine learning
touches almost every area of artificial intelligence as a target
competence or an enabling technology. Since it is a rapidly growing
area that is driving pervasive technological change, machine learning
has developed a variety of its own sub-fields, specialized technical
tools and methodologies. To counter the perception that machine
learning research is diverging from the interests of other areas of
artificial intelligence, a strong presence in machine learning will be
maintained at IJCAI-15. In addition to highlighting top quality
research, the Machine Learning Track will also emphasize research that
connects to other areas of artificial intelligence.

Submissions are therefore invited on significant, original, and
previously unpublished research on all aspects of machine learning,
with a special encouragement for machine learning research that
demonstrates clear relevance to other areas of artificial intelligence
research. General areas of interest include, but are not limited to:
probabilistic models and methods, large margin and kernel methods,
deep learning and neural learning, ensemble methods, learning from
partial labellings, unsupervised learning, relation learning and
graphs, reinforcement learning and on-line learning, learning in games
and multi-agent systems, evolutionary learning and nature inspired
learning, learning theory and machine learning applications. We
particularly welcome papers that formulate "new problems" for machine
learning and artificial intelligence research, in addition to more
traditional papers that propose "solutions" to established problems.
Such "new problem" papers will be assessed in terms of the clarity of
the proposed formulation, strength of the motivation, depth of the
challenges identified, and feasibility of the problems. Such papers
can provide value for the community identifying new paths to advancing
Artificial Intelligence. We would also like to draw attention to the
IJCAI-15 theme of "AI and the Arts" and encourage machine learning
submissions that are relevant to this theme.


All papers submitted to the Machine Learning track are regarded as
regular submissions to IJCAI 2015. Please consult the main IJCAI 2015
Call For Papers at http://ijcai-15.org/index.php/call-for-papers for
important dates, detailed submission instructions, (including
formatting guidelines and electronic templates), review process, and
important policies (on multiple submissions, confidentiality and
conflict of interest).

IJCAI 2015 Machine Learning Track Co-chairs:

Dale Schuurmans (University of Alberta, Canada)
Zhi-Hua Zhou (Nanjing University, China)

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