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math.OC2026
Neural feedback approximation for stochastic control with degenerate diffusions: error estimates and numerical analysis
Olivier Bokanowski, Jean-François Chassagneux, Marco Scaratti +1
We study finite-horizon stochastic optimal control problems and approximate the resulting time-discrete formulation by a direct policy-learning problem over neural-network feedback…
math.OC2026
Saddle Networks: Structure-Preserving Architectures for Convex-Concave Functions
Xavier Warin
Saddle-point models arise throughout optimization, optimal transport, robust learning, and control. In many applications, the relevant function f(x,y) is convex in x and concave in…
math.OC2026
Learning operators on labelled conditional distributions with applications to mean field control of non exchangeable systems
Samy Mekkaoui, Huyên Pham, Xavier Warin
We study the approximation of operators acting on probability measures on a product space with prescribed marginal. Let be a label space endowed with a reference measure , a…