Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization

ICML 2018 Umut SimsekliCagatay YildizThan Huy NguyenTaylan CemgilGael Richard

Recent studies have illustrated that stochastic gradient Markov Chain Monte Carlo techniques have a strong potential in non-convex optimization, where local and global convergence guarantees can be shown under certain conditions. By building up on this recent theory, in this study, we develop an asynchronous-parallel stochastic L-BFGS algorithm for non-convex optimization... (read more)

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