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AISTATS*2014 Call for Papers

Seventeenth International Conference on Artificial Intelligence and Statistics

April 22 - 25, 2014, Reykjavik, Iceland
Colocated with a MLSS Machine Learning Summer School

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. We encourage the submission of all papers which are in keeping with this objective at http://www.aistats.org.

Keynote Speakers:

Peter Bühlmann, ETH Zürich
Talk title: High-dimensional Causal Inference

Andrew Gelman, Columbia University
Talk title: Weakly Informative Priors: When a little information can do a lot of regularizing

Michael I. Jordan, University of California, Berkeley
Talk title: On the Computational and Statistical Interface and "Big Data"

See the Keynote Speakers page for abstracts of the keynotes.

Tutorial Speakers:

Roderick Murray-Smith, University of Glasgow
Talk title: Machine learning and Human Computer Interaction

Christian P. Robert, Ceremade - Université Paris-Dauphine
Talk title: Approximate Bayesian computation (ABC), methodology and applications

Håvard Rue, Norwegian University of Science and Technology
Talk title: Bayesian computing with INLA

See the Tutorials page for abstracts of the tutorials.

Paper Submission:

Proceedings track: This is the standard AISTATS paper submission track. Papers will be selected via a rigorous double-blind peer-review process. All accepted papers will be presented at the Conference as contributed talks or as posters and will be published in the Proceedings. A selected set of papers will be designated as "notable papers" which will be clearly distinguished in the Proceedings.

Highlight talks track: We will include talks on recent high-impact work on AISTATS themes. This is an opportunity to raise discussion and get additional exposure to work already published in journals. The talks will be selected based on one-page abstracts and the existing papers, and they do not lead to a paper in the Proceedings.

Late-breaking posters track: Some time at the conference will be set aside for "breaking news" posters having a one-page abstract. These are reports on ongoing or unpublished projects, projects already published elsewhere, partially developed ideas, negative results etc, and are meant as informal forums to encourage discussion. 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.

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.html.

Submission Requirements for Proceedings Track:

Electronic submission of papers is required. Papers may be up to 8 double-column pages in length, excluding references. Authors may optionally submit also supplementary material. Formatting and submission information is available at http://www.aistats.org/submit.html.

All accepted papers will be presented at the Conference either as contributed talks or as posters, and will be published in the AISTATS Conference Proceedings in the Journal of Machine Learning Research Workshop and Conference Proceedings series. Papers for talks and posters will be treated equally in publication.

Submission Deadlines:

Submissions will be considered if they are received by the following strict deadlines.

Proceedings track paper submissions:	1 November, 2013, 23:59 UTC
Highlight talk abstract submissions:	24 January, 2014, 23:59 UTC
Late-breaking poster abstract submissions:	24 January, 2014, 23:59 UTC

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

Colocated Events:

A Machine Learning Summer School (MLSS) will be held after the conference (April 26th-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:

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 geysirs and thermal pools. This is a unique opportunity to spend an AISTATS afternoon break at a geothermal warm beach, the famous Blue Lagoon.

Reykjavik is easily reachable by several airlines; travel information will be available on 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:

Edoardo Airoldi, Harvard University
Florence d'Alche-Buc, Université d'Evry-Val d'Essonne
Cédric Archambeau, Amazon
Peter Auer, University of Leoben
Erik Aurell, KTH
Yoshua Bengio, Université de Montréal
Carlo Berzuini, University of Manchester
Jeff A. Bilmes, University of Washington
Wray Buntine, NICTA
Lawrence Carin, Duke University
Guido Consonni, Università Cattolica del Sacro Cuore
Koby Crammer, The Technion
Emily B. Fox, University of Washington
Mehmet Gönen, Sage Bionetworks
Aapo Hyvärinen, University of Helsinki
Timo Koski, KTH
John Paisley, Columbia University
Jan Peters, Technische Universität Darmstadt
Volker Roth, Universität 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.