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Reimplemented proximal gradient method (PGM).

Jens Lucht requested to merge prox-grad-method into master

Improved usability and switched to explicit x dependence in functional F.

Furthermore,

  • switching to out-of-place instead of in-place tensor operations,
  • implemented two different strategies for Barzilai-Borwein step sizes,
  • corrected stopping condition if proximal operator G is not the identity,
  • moved setup, initialization of backtracking, gradient clearing into algorithms code; application now just need to call the __call__ method with desired iterations or tolerance.

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