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cs.LG2023
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
Yucen Lily Li, Tim G. J. Rudner, Andrew Gordon Wilson
Bayesian optimization is a highly efficient approach to optimizing objective functions which are expensive to query. These objectives are typically represented by Gaussian process…
cs.LG2020★ 1 cited
Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods
Nimar S. Arora, Nazanin Khosravani Tehrani, Kinjal Divesh Shah +7
Single-site Markov Chain Monte Carlo (MCMC) is a variant of MCMC in which a single coordinate in the state space is modified in each step. Structured relational models are a good c…