Local Kernels That Approximate Bayesian Regularization and Proximal Operators
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2019.2893071
Abstract: In this paper, we broadly connect kernel-based filtering (e.g., approaches such as the bilateral filter and non-local means, but also many more) with general variational formulations of Bayesian regularized least squares and the related concept… read more here.
Keywords: proximal; kernels approximate; proximal operators; local kernels ... See more keywords
Entropic Proximal Operators for Nonnegative Trigonometric Polynomials
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2018.2862399
Abstract: Signal processing applications of semidefinite optimization are often rooted in sum-of-squares representations of nonnegative trigonometric polynomials. Interior-point solvers for semidefinite optimization can handle constraints of this form with a per-iteration-complexity that is cubic in the… read more here.
Keywords: entropic proximal; trigonometric polynomials; distance; proximal operators ... See more keywords