A Complete Recipe for Stochastic Gradient MCMC
作者： Tianqi Chen , Emily B. Fox , Yi-An Ma
DOI:
关键词: Riemann hypothesis 、 Mathematical optimization 、 Gradient noise 、 Hybrid Monte Carlo 、 Markov process 、 Mathematics 、 Leverage (statistics) 、 Applied mathematics 、 Scalability 、 Continuous-time stochastic process 、 Markov chain Monte Carlo
摘要: Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous dynamics to define a transition kernel that efficiently explores a target distribution. In tandem, a focus has …
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