Non-asymptotic bounds for modified tamed unadjusted Langevin algorithm in non-convex setting
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...
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Main Author: | Ng, Matthew Cheng En |
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Other Authors: | Ariel Neufeld |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
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Online Access: | https://hdl.handle.net/10356/156899 |
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Institution: | Nanyang Technological University |
Language: | English |
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