no code implementations • NeurIPS 2021 • Carson Kent, Jiajin Li, Jose Blanchet, Peter W. Glynn
We propose a novel Frank-Wolfe (FW) procedure for the optimization of infinite-dimensional functionals of probability measures - a task which arises naturally in a wide range of areas including statistical learning (e. g. variational inference) and artificial intelligence (e. g. generative adversarial networks).