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pro vyhledávání: '"South, Leah F."'
In Deep Reinforcement Learning models trained using gradient-based techniques, the choice of optimizer and its learning rate are crucial to achieving good performance: higher learning rates can prevent the model from learning effectively, while lower
Externí odkaz:
http://arxiv.org/abs/2410.12598
Markov chain Monte Carlo (MCMC) is the engine of modern Bayesian statistics, being used to approximate the posterior and derived quantities of interest. Despite this, the issue of how the output from a Markov chain is post-processed and reported is o
Externí odkaz:
http://arxiv.org/abs/2103.16048
The numerical approximation of posterior expected quantities of interest is considered. A novel control variate technique is proposed for post-processing of Markov chain Monte Carlo output, based both on Stein's method and an approach to numerical in
Externí odkaz:
http://arxiv.org/abs/2002.00033
This is a contribution for the discussion on "Unbiased Markov chain Monte Carlo with couplings" by Pierre E. Jacob, John O'Leary and Yves F. Atchad\'e to appear in the Journal of the Royal Statistical Society Series B.
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Externí odkaz:
http://arxiv.org/abs/1912.10496
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Bayesian synthetic likelihood (BSL) is a popular method for estimating the parameter posterior distribution for complex statistical models and stochastic processes that possess a computationally intractable likelihood function. Instead of evaluating
Externí odkaz:
http://arxiv.org/abs/1907.10940
Zero-variance control variates (ZV-CV) are a post-processing method to reduce the variance of Monte Carlo estimators of expectations using the derivatives of the log target. Once the derivatives are available, the only additional computational effort
Externí odkaz:
http://arxiv.org/abs/1811.05073
We introduce a new class of sequential Monte Carlo methods called nested sampling via sequential Monte Carlo (NS-SMC), which reformulates the essence of the nested sampling method of Skilling (2006) in terms of sequential Monte Carlo techniques. This
Externí odkaz:
http://arxiv.org/abs/1805.03924
Akademický článek
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Publikováno v:
Annual Review of Statistics & Its Application; Mar2022, Vol. 9, p529-555, 78p
