3 papers
math.OC2026
Finite-Sample Metric Non-Collapse for Geometrically Supervised Latent World Models in Control
Alain Bensoussan, Minh-Nhat Phung, Minh-Binh Tran
We establish a finite-sample learning-to-control theory for geometrically supervised latent models of nonlinear deterministic systems. Geometric supervision is used only during tra…
cs.LG2025
A Relative Ignorability Framework for Decision-Relevant Observability in Control Theory and Reinforcement Learning
MaryLena Bleile, Minh-Nhat Phung, Minh-Binh Tran
Sequential decision-making systems routinely operate with missing or incomplete data. Classical reinforcement learning theory, which is commonly used to solve sequential decision p…
math.OC2019
Barycenters in the Hellinger-Kantorovich space
Nhan-Phu Chung, Minh-Nhat Phung
Recently, Liero, Mielke and Savaré introduced Hellinger-Kantorovich distance on the space of nonnegative Radon measures of a metric space [19,20]. We prove that Hellinger-Kanto…