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On Quasi-Newton Forward-Backward Splitting: Proximal Calculus and Convergence
We introduce a framework for quasi-Newton forward-backward splitting algorithms (proximal quasi-Newton methods) with a metric induced by diagonal $\pm$ rank-$r$ symmetric positive definite matrices. This special type of metric allows for a highly efficient evaluation of the proximal mapping. The key to this efficiency is a general proximal calculus in …