This repository contains the numerical work related to the article, A conditional-gradient-based single-loop augmented Lagrangian method for inequality constrained optimization, by Xiaozhou Wang, Ting ...
Abstract: Decentralized learning is a distributed learning approach, wherein clients collaborate to learn a global model. Many optimization problems that appear in signal processing and machine ...
Abstract: We propose a variant of the classical conditional gradient method (CGM) for sparse inverse problems with differentiable measurement models. Such models arise in many practical problems ...
where K is an operator associated with a linear PDE. It employs the method described in the paper "Linear convergence of a one-cut conditional gradient method for total variation regularization".
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