8 citations · 8 across the 6 of their papers we have counts for
4 papers · 1 filter
Continuous-Time Trajectory Generation from Discrete Observations with Stochasticity
Ruifeng Shang, Shu Liu, Yuhua Zhu
Physical systems evolve continuously in time, yet their states are typically observed only at discrete times. Generating trajectories consistent with their probability densities fr…
Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1
This paper develops a model-free framework for continuous-time mean-field control when the population evolves according to unknown controlled McKean--Vlasov dynamics and only discr…
Policy Gradient for Continuous-Time Mean-Field Control
Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1
This paper develops a policy gradient method for entropy-regularized mean-field control in the discounted infinite-horizon setting. We consider randomized feedback policies and a c…
Stabilizing Policy Optimization via Logits Convexity
Hongzhan Chen, Tao Yang, Yuhua Zhu +3
While reinforcement learning (RL) has been central to the recent success of large language models (LLMs), RL optimization is notoriously unstable, especially when compared to super…