Pierre Henry-Labord`ere
Published 2019-04-09Version 1
In this paper, we introduce a primal-dual algorithm for solving (martingale) optimal transportation problems, with cost functions satisfying the twist condition, close to the one that has been used recently for training generative adversarial networks. As some additional applications, we consider anomaly detection and automatic generation of financial data.
Universal Approximation of Parametric Optimization via Neural Networks with Piecewise Linear Policy Approximation
A primal-dual algorithm with optimal stepsizes and its application in decentralized consensus optimization
A Primal-dual algorithm for image reconstruction with ICNNs
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