SAMS - Sparsity in Applied Mathematics and Statistics
In recent years the acquisition of big data sets on one hand and the increasing popularity of high-dimensional models on the other hand have intensified the interdisciplinary contacts between data sciences, machine learning, statistics, applied mathematics, computer science and signal processing. The learning or estimation of patterns and structures from massive observations in complex models is closely related to the solution of possibly large, ill posed or ill conditioned inverse problems. The understanding of graphical and structured models involves expertise in the algorithmic, numerical and statistical aspects. Regularisation of ill posed or ill conditioned problems is often based on an explicit or implicit assumption of sparsity, which can be imposed already at the recovery of the data, as in compressed sensing.
The goal of this workshop is to bring together several experts in the various fields of expertise.
• Sparsity (theory, algorithms, applications, ...)
• High-dimensional models
• Inverse problems
• Compressed sensing
• Statistical modelling of high-dimensional data
• Networks and graphical models
• (Medical) Imaging
• Model and variable selection; structured or group selection
• Statistical learning
• Optimization (in sparse/inverse problems or high-dimensional data)
• Algorithms for the above mentioned problems
• Laure Blanc-Feraud, Université de Nice-Sophia Antipolis, France
• Ivan Markovsky, Vrije Universiteit Brussel, Belgium
• Richard Samworth, Cambridge University, UK
• Goeran Kauermann, Ludwig-Maximilians-Universität München, Germany
• Francesco Stingo, Università degli Studi di Firenze, Italy
Registration is free (and includes two lunches), but mandatory.
Please register by filling in the registration form (see more info )
The registration form includes the option to submit an abstract for a contributed talk (20 to 30 minutes, depending on the number of registrations).
The organizers encourage in particular young researchers to submit a talk.
Registration and abstract submission deadline is April 15, 2017
As the workshop is free, and the capacity is not unlimited, we kindly yet firmly ask you to consider registration as a commitment to participate during the full conference, to cancel participation only for good reasons and in that case, to inform us as soon as possible at the email address below