22 citations · 29 across the 6 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
stat.ML2020★ 22 cited
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo
Mert Gürbüzbalaban, Xuefeng Gao, Yuanhan Hu +1
Stochastic gradient Langevin dynamics (SGLD) and stochastic gradient Hamiltonian Monte Carlo (SGHMC) are two popular Markov Chain Monte Carlo (MCMC) algorithms for Bayesian inferen…
math.OC2020★ 4 cited
Non-Convex Optimization via Non-Reversible Stochastic Gradient Langevin Dynamics
Yuanhan Hu, Xiaoyu Wang, Xuefeng Gao +2
Stochastic Gradient Langevin Dynamics (SGLD) is a powerful algorithm for optimizing a non-convex objective, where a controlled and properly scaled Gaussian noise is added to the st…
cs.LG2020★ 2 cited
Fractional moment-preserving initialization schemes for training deep neural networks
Mert Gurbuzbalaban, Yuanhan Hu
A traditional approach to initialization in deep neural networks (DNNs) is to sample the network weights randomly for preserving the variance of pre-activations. On the other hand,…