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"Markov Chain Monte Carlo"
Distributed Bayesian learning with stochastic natural gradient expectation propagation and the posterior server
This paper makes two contributions to Bayesian machine learning algorithms. Firstly, we propose stochastic natural gradient expectation …
Leonard Hasenclever
,
Stefan Webb
,
Thibaut Lienart
,
Sebastian Vollmer
,
Balaji Lakshminarayanan
,
Charles Blundell
,
Yee Whye Teh
Cite
Consistency and fluctuations for stochastic gradient Langevin dynamics
Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally expensive. Both the calculation of …
Yee Whye Teh
,
Alexandre H Thiery
,
Sebastian J Vollmer
Cite
Consistency and fluctuations for stochastic gradient Langevin dynamics
Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally expensive. Both the calculation of …
Yee Whye Teh
,
Alexandre H Thiery
,
Sebastian J Vollmer
Cite
Exploration of the (non-)asymptotic bias and variance of stochastic gradient langevin dynamics
Applying standard Markov chain Monte Carlo (MCMC) algorithms to large data sets is computationally infeasible. The recently proposed …
Sebastian J Vollmer
,
Konstantinos C Zygalakis
,
Yee Whye Teh
Cite
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