Another few notes to myself:

- The paper Variational properties of value functions by Aleksandr Y. Aravkin, James V. Burke and Michael P. Friedlander deal with the value function for regularization functionals. Could be useful in the derivation and analysis of heuristic parameter choice rules.
- The paper Optimization with First-Order Surrogate Functions by Julien Mairal analyzes “surrogate functional minimization” is a quite broad sense and it also seems to be applicable to non-convex problems.
- The paper A fast randomized Kaczmarz algorithm for sparse solutions of consistent linear systems by Hassan Mansour, Ozgur Yilmaz proposes an extension of the Kaczmarz method to calculate sparse solutions by pruning the support during iteration.
- The paper Enhanced Compressed Sensing Recovery With Level Set Normals by Virginia Estellers, Jean-Philippe Thiran and Xavier Bresson describes, how estimates of normals of level sets can be used the to enhance sparse reconstruction.

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