2 papers
math.OC2026
Mathematical methods of reinforcement learning
Denis Belomestny, Alexander Gasnikov, Egor Gladin +5
Reinforcement learning (RL) is increasingly grounded in tools from probability, optimization, and operator theory. This survey organizes the mathematical structures that underpin t…
math.OC2021
Flexible Modification of Gauss-Newton Method and Its Stochastic Extension
Nikita Yudin, Alexander Gasnikov
This work presents a novel version of recently developed Gauss-Newton method for solving systems of nonlinear equations, based on upper bound of solution residual and quadratic reg…