Non-asymptotic bounds for modified tamed unadjusted Langevin algorithm in non-convex setting

• Main Author: Ng, Matthew Cheng En
• Other Authors: Ariel Neufeld
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Science::Mathematics::Probability theory; Science::Mathematics::Applied mathematics
• Online Access: https://hdl.handle.net/10356/156899
• Institution: Nanyang Technological University

We consider the problem of sampling from a target distribution $\pi_\beta$ on $\mathbb{R}^d$ with density proportional to $\theta\mapsto e^{-\beta U(\theta)}$ using explicit numerical schemes based on discretising the Langevin stochastic differential equation (SDE). In recent literature, taming has...