4 papers
Revisiting Bayesian Variable Selection via Optimization
Leo L Duan
Variable selection in linear regression has been a central topic in statistical research for decades. Bayesian variable selection methods, which account for uncertainty in both the…
Bayesian Distance-to-Set Models: from Latent Variable to Latent Projection
Leo L Duan, Yuexi Wang, Jason Xu
Statistical models often assume that data are generated near a structured, smooth, or low-dimensional set. A common approach is to use Bayesian latent variable models, in which eac…
Exact Sampling of Spanning Trees via Fast-forwarded Random Walks
Edric Tam, David B. Dunson, Leo L. Duan
Tree graphs are routinely used in statistics. When estimating a Bayesian model with a tree component, sampling the posterior remains a core difficulty. Existing Markov chain Monte…
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples
Leo L. Duan, Anirban Bhattacharya
It has become increasingly easy nowadays to collect approximate posterior samples via fast algorithms such as variational Bayes, but concerns exist about the estimation accuracy. I…