48 citations · 153 across the 26 of their papers we have counts for
7 papers · 1 filter
PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols
Fabrizio Cicala, Weicheng Wang, Tianhao Wang +4
Many proximity-based tracing (PCT) protocols have been proposed and deployed to combat the spreading of COVID-19. In this paper, we take a systematic approach to analyze PCT protoc…
Markov Neighborhood Regression for High-Dimensional Inference
Faming Liang, Jingnan Xue, Bochao Jia
This paper proposes an innovative method for constructing confidence intervals and assessing p-values in statistical inference for high-dimensional linear models. The proposed meth…
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
Wei Deng, Guang Lin, Faming Liang
We propose an adaptively weighted stochastic gradient Langevin dynamics algorithm (SGLD), so-called contour stochastic gradient Langevin dynamics (CSGLD), for Bayesian learning in…
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Wei Deng, Qi Feng, Georgios Karagiannis +2
Replica exchange stochastic gradient Langevin dynamics (reSGLD) has shown promise in accelerating the convergence in non-convex learning; however, an excessively large correction f…
Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts
Sehwan Kim, Qifan Song, Faming Liang
Bayesian deep learning offers a principled way to address many issues concerning safety of artificial intelligence (AI), such as model uncertainty,model interpretability, and predi…
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng, Qi Feng, Liyao Gao +2
Replica exchange Monte Carlo (reMC), also known as parallel tempering, is an important technique for accelerating the convergence of the conventional Markov Chain Monte Carlo (MCMC…