AISTATS*2013 Call for Papers
Sixteenth International Conference on
Artificial Intelligence and Statistics
April 29 - May 1, 2013, Scottsdale, AZ, USA
DoubleTree Paradise Valley Resort
Colocated with the International Conference on Learning Representations
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 www.aistats.org.
Papers will be selected via a rigorous double-blind peer-review process, including expanded author feedback. All accepted papers will be presented at the Conference as contributed talks or as posters. Highlights of the review process this year:
- There will be a primary and secondary member of the senior program committee in charge of a paper, with discussion triggers given the ratings and content of the reviews.
- Following the lead of ICML 2012, reviewers will be assigned to a paper using multiple mechanisms so that there is no "single point of failure": one by an automated mechanism, and one each by the primary and secondary members of the SPC.
- Following the lead of AISTATS 2011, a select but non-trivial set of papers will be designated as "notable papers". These will carry a preface in the proceedings by a member of the senior program committee, and will also be given greater visibility and discussion via social media.
- We are also working with certain journals to facilitate transfer of reviews+reviewer-names for the notable papers, should the authors choose to submit extended journal versions.
We hope these changes motivate authors to submit their most innovative work at the intersection of statistics and artificial intelligence to the conference.
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 this page
Electronic submission of papers is required. Papers may be up to 8
double-column pages in length, excluding references; formatting and
submission information will be made available on the conference website at submit.html.
Submissions will be considered if they are received by 23:59, November 15th,
2012, UTC. See the conference website for additional important dates: date.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. Papers for talks and posters will be treated equally in publication.
Submitted manuscripts should not have been previously published in a journal or in the proceedings of a conference, and should not be under consideration for publication at another conference at any point during the AISTATS review process. It is acceptable to have a substantially extended version of the submitted paper under consideration simultaneously for journal publication, so long as the journal version's planned publication date is in 2013 or later, the journal submission does not interfere with AISTATS's right to publish the paper, and the situation is clearly described at the time of AISTATS submission. Please describe the situation in the appropriate box on the submission page (and do not include author information in the submission itself, to avoid accidental unblinding).
- Carlos M. Carvalho, McCombs School of Business and Division of Statistics and Scientific Computation, The University of Texas at Austin.
- Pradeep Ravikumar, Department of Computer Science and Division of Statistics and Scientific Computation, The University of Texas at Austin.
If you would like to post the call for papers in your department, here is a flyer
(1 page, PDF).