Workshop on Sparsity in Machine Learning and Statistics
Cumberland Lodge, UK
1 – 3 April 2009
CALL FOR PAPERS
Sparse estimation is playing an increasingly important role in the statistics and machine learning communities. Several methods have recently been developed in both fields, which rely upon the notion of sparsity (e.g.penalty methods like the Lasso, the Winnow algorithm, linear programming boosting, Dantzig selector, etc.), which can be thought of as a mathematical version of Occam’s razor. Many of the key theoretical ideas and statistical analysis of the methods have been developed independently, but there is increasing awareness of the potential for cross-fertilization of ideas between statistics and machine learning. Sparse estimation is starting to have an important impact on applied areas also, with applications ranging from biostatistics, medical imaging, to geoscience and finance. To bring together results on sparsity from different applied and theoretical fields of machine learning and statistics, we are planning to hold a workshop on 1-3rd April 2009 at Cumberland Lodge, UK.
The Invited Speakers include:
– Nicolò Cesa-Bianchi (Università degli Studi di Milano),
– Sara van de Geer (TBC) (ETH Zurich),
– Charles Micchelli (TBC) (State University of New York)
– Jared Tanner (University of Edinburgh),
– Alexandre Tsybakov (CREST and Université Paris VI),
– Jon Wellner (University of Washington),
– David Wipf (University of California),
– Ming Yuan (Georgia Tech College of Engineering),
and each invited speaker will give an hour long presentation, on different aspects of sparse estimation. In addition to the invited lectures there will be a number of contributed presentations, and a poster session. We invite you to submit a full page extended abstract, with pointers to reference material where appropriate. Submissions should be sent to email@example.com and should be received by Thursday 15 January 2009. Notification of acceptance will be given on Friday 30 January 2009.
See also http://www.cs.ucl.ac.uk/staff/rmartin/smls09/
Papers will be selected for oral or poster presentation.
Sofia Olhede, Massimiliano Pontil & John Shawe-Taylor