Bregman Proximal Mappings and Bregman–Moreau Envelopes Under Relative Prox-Regularity

Emanuel Laude, Peter Ochs, Daniel Cremers

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


We systematically study the local single-valuedness of the Bregman proximal mapping and local smoothness of the Bregman–Moreau envelope of a nonconvex function under relative prox-regularity—an extension of prox-regularity—which was originally introduced by Poliquin and Rockafellar. As Bregman distances are asymmetric in general, in accordance with Bauschke et al., it is natural to consider two variants of the Bregman proximal mapping, which, depending on the order of the arguments, are called left and right Bregman proximal mapping. We consider the left Bregman proximal mapping first. Then, via translation result, we obtain analogue (and partially sharp) results for the right Bregman proximal mapping. The class of relatively prox-regular functions significantly extends the recently considered class of relatively hypoconvex functions. In particular, relative prox-regularity allows for functions with a possibly nonconvex domain. Moreover, as a main source of examples and analogously to the classical setting, we introduce relatively amenable functions, i.e. convexly composite functions, for which the inner nonlinear mapping is component-wise smooth adaptable, a recently introduced extension of Lipschitz differentiability. By way of example, we apply our theory to locally interpret joint alternating Bregman minimization with proximal regularization as a Bregman proximal gradient algorithm, applied to a smooth adaptable function.

Original languageEnglish
Pages (from-to)724-761
Number of pages38
JournalJournal of Optimization Theory and Applications
Issue number3
StatePublished - 1 Mar 2020


  • Amenable functions
  • Bregman proximal mapping
  • Bregman–Moreau envelope
  • Prox-regularity


Dive into the research topics of 'Bregman Proximal Mappings and Bregman–Moreau Envelopes Under Relative Prox-Regularity'. Together they form a unique fingerprint.

Cite this