I am planning to lead a very informal discussion on some neat techniques for convex and semidefinite relaxation that can be used to transform intractable optimization problems into approximate but convex ones. I'll also discuss a few applications to statistical neuroscience that we are currently pursuing.
Some background material (although I'm not planning to go over any of these in detail) includes:
http://www.se.cuhk.edu.hk/~manchoso/papers/sdrapp-SPM.pdf
http://arxiv.org/abs/1012.0621
http://www-stat.stanford.edu/~candes/papers/PhaseRetrieval.pdf
http://users.cms.caltech.edu/~jtropp/papers/MT11-Two-Proposals-EJS.pdf
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