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| − | {{Event
| + | I'm quite plaseed with the information in this one. TY! |
| − | | Acronym = AISTATS 2009
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| − | | Title = Twelfth International Conference on Artificial Intelligence and Statistics
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| − | | Type = Conference
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| − | | Series =
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| − | | Field = Artificial intelligence
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| − | | Homepage =
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| − | | Start date = Apr 16, 2009
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| − | | End date = Apr 19, 2009
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| − | | City= Clearwater
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| − | | State = Florida
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| − | | Country = USA
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| − | | Abstract deadline =
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| − | | Submission deadline = Nov 5, 2008
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| − | | Notification =
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| − | <pre>
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| − | AISTATS*09 Call for Papers
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| − | Twelfth International Conference on Artificial Intelligence and Statistics
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| − | April 16-19, 2009, Clearwater, Florida USA
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| − | This is the twelfth conference on Artificial Intelligence and Statistics, an interdisciplinary gathering of researchers at the intersection of computer science, statistics, and related areas. Since its inception in 1985, the primary goal of this conference has been to broaden research in both of these fields by promoting the exchange of ideas between them. We encourage the submission of all papers which are in keeping with this objective.
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| − | Presentations will include invited talks, contributed talks, and posters. Papers for poster sessions will be treated equally with papers for oral presentation in publications.
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| − | Papers on all aspects of the interface between AI & Statistics are strongly encouraged, including but not limited to:
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| − | * Active learning and experimental design
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| − | * Approximate and Monte Carlo Inference
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| − | * Bayesian statistics
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| − | * Causal modelling
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| − | * Density Estimation
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| − | * Information retrieval
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| − | * Game theory
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| − | * Cluster analysis and unsupervised learning
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| − | * Graphical models
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| − | * Integrated man-machine modeling methods
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| − | * Interpretability in modelling
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| − | * Kernel methods
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| − | * Knowledge discovery in databases
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| − | * Metadata and the design of statistical data bases
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| − | * Model uncertainty, multiple models
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| − | * Online learning
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| − | * Pattern recognition
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| − | * Prediction: classification and regression
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| − | * Probability and search
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| − | * Semi-supervised learning
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| − | * Statistical decision making
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| − | * Vision, robotics, natural language processing, speech recognition
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| − | * Visualization of very large datasets
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| − | | |
| − | Submission Requirements:
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| − | Papers may be up to 8 double-column pages in length, and must be submitted electronically by 23:59, Wednesday November 5, 2008, Universal Time.
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| − | Acceptance notices will be emailed by early January, and camera-ready final versions (same format) will be due in late February 2009. These papers will published in the refereed conference proceedings.
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| − | For more information, see the AI and Statistics Webpage: http://www.ics.uci.edu/~aistats/
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| − | Program Chairs
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| − | * David van Dyk, University of California, Irvine
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| − | * Max Welling, University of California, Irvine
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| − | | |
| − | </pre>This CfP was obtained from [http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=3503&copyownerid=1398 WikiCFP][[Category:Statistics]]
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| − | [[Category:Machine learning]]
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