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

• المؤلف الرئيسي: Ng, Matthew Cheng En
• مؤلفون آخرون: Ariel Neufeld
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2022
• الموضوعات: Science::Mathematics::Probability theory; Science::Mathematics::Applied mathematics
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/156899
• المؤسسة: 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...