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Journal Club: Proximal Algorithms

This Journal Club we'll be looking at Proximal Algorithms!

Proximal algorithms generalize the concept of the orthogonal projection of a point onto a set C.  They can be especially useful when dealing with a complicated-looking optimization scheme (which often arise from machine learning and signal processing problems), where they help decompose the complicated scheme into a sequence of much simpler optimization steps which, when updated in an iterative fashion, provide a solution to the original problem.

We'll be basing our discussion and review on the tutorial paper by Boyd below:

http://www.stanford.edu/~boyd/papers/pdf/prox_algs.pdf

You can find commented code for many of the examples in the paper on the authors' website:

http://www.stanford.edu/~boyd/papers/prox_algs.html



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