Than Huy Nguyen — accepted AI-conference papers

2019

Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization

Than Huy Nguyen, Umut Simsekli, Gael Richard

ICML 2019oral

Recent studies on diffusion-based sampling methods have shown that Langevin Monte Carlo (LMC) algorithms can be beneficial for non-convex optimization, and rigorous theoretical guarantees have been proven for both asymptotic and finite-time regimes. Algorithmically, LMC-based algorithms resemble the…

Cited by 36 Source ↗PDF ↗Scholar ↗

2018

Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization

Umut Simsekli, Cagatay Yildiz, Than Huy Nguyen, Taylan Cemgil, Gael Richard

ICML 2018oral

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 asy…

Cited by 27 Source ↗PDF ↗Scholar ↗