2 papers
stat.ML2026
Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
Dorival Leão, Alberto Ohashi, Simone Scotti +1
This paper studies continuous-time stochastic control problems whose controlled states are fully non-Markovian and depend on unknown model parameters. Such problems arise naturally…
math.PR2025
Forward stochastic integration for adapted processes w.r.t. Riemann-Liouville fractional Brownian motion (Full version)
Paulo Henrique da Costa, Alberto Ohashi, Francesco Russo
This paper provides the time-dependent -martingale representation of the forward stochastic integral where the driving noise is the Riemann-Liouville fractional Brownian motio…