3 papers
math.OC2026
Robust Exploratory Stopping under Ambiguity in Reinforcement Learning
Junyan Ye, Hoi Ying Wong, Kyunghyun Park
We propose and analyze a continuous-time robust reinforcement learning framework for optimal stopping under ambiguity. In this framework, an agent chooses a robust exploratory stop…
math.OC2026
Duality and DeepMartingale for High-Dimensional Optimal Switching: Computable Upper Bounds and Approximation-Expressivity Guarantees
Junyan Ye, Hoi Ying Wong
We study finite-horizon optimal switching with discrete intervention dates on a general filtration, allowing continuous-time observations between decision dates, and develop a deep…
math.OC2026
DeepMartingale: Duality of the Optimal Stopping Problem with Expressivity and High-Dimensional Hedging
Junyan Ye, Hoi Ying Wong
We propose \textit{DeepMartingale}, a deep-learning framework for the dual formulation of discrete-monitoring optimal stopping problems under continuous-time models. Leveraging a m…