Connectionists: AISTATS: Second call for late-breaking posters, DL Jan 24

[Peltonen Jaakko]

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AISTATS 2014 Call for Late-breaking Posters
Seventeenth International Conference on Artificial Intelligence and Statistics
April 22 - 25, 2014, Reykjavik, Iceland
http://www.aistats.org

Colocated with a MLSS Machine Learning Summer School
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AISTATS is an interdisciplinary gathering of researchers at the intersection
of computer science, artificial intelligence, machine learning, statistics,
and related areas. Since its inception in 1985, the primary goal of AISTATS
has been to broaden research in these fields by promoting the exchange of
ideas among them.

Some time at AISTATS will be set aside for "breaking news" posters having a
one-page abstract. These posters may report on ongoing or unpublished
projects, projects already published elsewhere, partially developed ideas,
negative results etc, and are meant as informal forums to encourage
discussion. Abstracts should summarize and highlight why the projects will be
of interest to the AISTATS community. The review process of the late-breaking
posters will be very light-touch and presentation at the Conference will not
lead to publication in the Proceedings. We encourage the submission of
late-breaking posters at http://www.aistats.org

In brief:
- Electronic submission of one-page abstracts is required.
- Include authors names as the reviewing is not double blind.
- Accepted submissions will be presented as posters but will not be published.
- The submission site will be open by 20 December.
- Submissions will be considered if received by 24 January, 2014, 23:59 UTC.
- Acceptance notifications will be emailed by February 11th.
- More details below and at http://www.aistats.org/submit_latebreaking_posters.php



Keynote and Tutorial Speakers:
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Keynote Speakers: 
Peter Buhlmann, ETH Zurich
Andrew Gelman, Columbia University
Michael I. Jordan, University of California, Berkeley

Tutorial Speakers: 
Roderick Murray-Smith, University of Glasgow
Christian P. Robert, Ceremade - Universite Paris-Dauphine
Havard Rue, Norwegian University of Science and Technology


Submission Requirements for Late-breaking Posters:
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Electronic submission of one-page abstracts is required. The abstracts must
fit one A4/letter page with sufficient margins and at least 10 point font
size. The authors may use the proceedings track paper format, but this is not
required. Please remember to include authors names as the reviewing is not
double blind.

Abstracts will be lightly reviewed. Acceptance notifications will be emailed
by February 11th. These will be presented as posters at the conference but
will not be published.

Solicited topics include, but are not limited to:

* Models and estimation: graphical models, causality, Gaussian processes,
  approximate inference, kernel methods, nonparametric models, statistical and
  computational learning theory, manifolds and embedding, sparsity and
  compressed sensing, ...
* Classification, regression, density estimation, unsupervised and
  semi-supervised learning, clustering, topic models, ...
* Structured prediction, relational learning, logic and probability
* Reinforcement learning, planning, control
* Game theory, no-regret learning, multi-agent systems
* Algorithms and architectures for high-performance computation in AI and
  statistics
* Software for and applications of AI and statistics

For a more detailed list of keywords, see http://www.aistats.org/keywords.php.

See http://www.aistats.org/submit_latebreaking_posters.php for submission
details.


Submission Deadline:
--------------------
Submissions will be considered if received by 24 January, 2014, 23:59 UTC.
Acceptance notifications will be emailed by February 11th.

See the conference website for additional important dates:
http://www.aistats.org/dates.php.


Colocated Events:
-----------------
A Machine Learning Summer School (MLSS) will be held after the conference
(April 25th-May 4th). April 25 will be an AISTATS/MLSS joint tutorial + MLSS
poster session day. The summer school features an exciting program with talks
from leading experts in the field, see http://mlss2014.hiit.fi for details.


Venue:
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AISTATS 2014 will be held in Reykjavik, the capital of Iceland, in Grand Hotel
Reykjavik. Reykjavik and its environs offer a unique mix of culture and varied
nature, from glaciers to waterfalls to geysers and thermal pools. This is a
unique opportunity to spend an afternoon break at the famous Blue Lagoon
geothermal warm beach. Travel information available at http://www.aistats.org.


Program Chairs:
---------------
Samuel Kaski, Aalto University and University of Helsinki
Jukka Corander, University of Helsinki

Local Chair: Deon Garrett,  School of Computer Science, Reykjavik University
and Icelandic Institute for Intelligent Machines

Senior Program Committee:
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Edoardo Airoldi, Harvard University; Florence d'Alche-Buc, Universite
d'Evry-Val d'Essonne; Cedric Archambeau, Amazon Peter Auer, University of
Leoben; Erik Aurell, KTH; Yoshua Bengio, Universite de Montreal; Carlo
Berzuini, University of Manchester; Jeff A. Bilmes, University of Washington;
Wray Buntine, NICTA; Lawrence Carin, Duke University; Guido Consonni,
Universita Cattolica del Sacro Cuore; Koby Crammer, The Technion; Emily B.
Fox, University of Washington; Mehmet Gonen, Sage Bionetworks; Aapo Hyvarinen,
University of Helsinki; Timo Koski, KTH; John Paisley, Columbia University;
Jan Peters, Technische Universitat Darmstadt; Volker Roth, Universitat Basel;
Yevgeny Seldin, Queensland University of Technology and UC Berkeley; Scott
Sisson, University of New South Wales; Suvrit Sra, Max-Planck Institute for
Intelligent Systems; Masashi Sugiyama, Tokyo Institute of Technology; Joe
Suzuki, Osaka University; Bill Triggs, Centre National de Recherche
Scientifique; Aki Vehtari, Aalto University; Jean-Philippe Vert, Mines
ParisTech and Curie Institute; Stephen Walker, University of Texas at Austin;
Kun Zhang, Max Planck Institute for Intelligent Systems

The European meetings of AISTATS are organized by the European Society for
Artificial Intelligence and Statistics.

============== for more information see http://www.aistats.org ===============