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".
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 ...
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 ...
Add a description, image, and links to the conditional-gradient-method topic page so that developers can more easily learn about it.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results