2 papers
stat.ML2026
Riemannian Langevin Dynamics: Strong Convergence of Geometric Euler-Maruyama Scheme
Zhiyuan Zhan, Masashi Sugiyama
Low-dimensional structure in real-world data plays an important role in the success of generative models, which motivates diffusion models defined on intrinsic data manifolds. Such…
cs.LG2024
Reinforcement Learning with Options and State Representation
Ayoub Ghriss, Masashi Sugiyama, Alessandro Lazaric
The current thesis aims to explore the reinforcement learning field and build on existing methods to produce improved ones to tackle the problem of learning in high-dimensional and…