arXiv:2506. 08121v2 Announce Type: replace-cross Abstract: We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and the optimal control are simultaneously updated through Langevin-type dynamics.
By Qi Feng, Gu Wang
arXiv:2608. 02844v1 Announce Type: cross Abstract: We develop a class of diffusion-based stochastic particle optimisation methods for loss functions with intractable gradients.
By Jiechen Jackie Zhang, O. Deniz Akyildiz
arXiv:2609.30274v1 Announce Type: new
Abstract: Machine Learning and more specifically Deep Learning involves solving large scale nonconvex optimization problems. Several algorithms have been propose...
By St\'ephane Galatolo, St\'ephane Chr\'etien
arXiv:2411. 01982v2 Announce Type: replace-cross Abstract: We study the problem of learning controlled stochastic differential equations (SDEs) \[ dX_t = b(t,X_t,u_t)\,dt + \sigma(t,X_t,u_t)\,dW_t, \] whose drift and diffusion depend nonlinearly on time, state, and control values.
By Luc Brogat-Motte, Riccardo Bonalli, Alessandro Rudi
arXiv:2604. 08580v2 Announce Type: replace-cross Abstract: Reward fine-tuning of diffusion and flow models and sampling from tilted or Boltzmann distributions can both be formulated as stochastic optimal control (SOC) problems, where learning an optimal generative dynamics corresponds to optimizing a control under SDE constraints.
By Carles Domingo-Enrich, Jiequn Han
The paper proves that the deep Galerkin method (DGM) converges when applied to Hamilton‑Jacobi‑Bellman equations derived from finite‑state mean field control problems. By showing that the DGM loss can be driven arbitrarily low under sufficient regularity of the value function, and that a vanishing loss forces uniform convergence of the neural network approximators to the true value function on the simplex, the authors establish both existence and convergence results for the DGM. Numerical experiments further illustrate the method’s ability to handle high‑dimensional HJB equations.
By William Hofgard, Jingruo Sun, Asaf Cohen