82 citations · 204 across the 14 of their papers we have counts for
18 papers
Fast approximate Bayesian multidimensional scaling with consistency guarantees
Ami Sheth, Aaron Smith, Andrew J. Holbrook
Bayesian multidimensional scaling (BMDS) embeds objects in a low-dimensional space to approximately preserve an observed dissimilarity matrix. Compared to classic MDS, BMDS is…
Mixing on Columns of the Transvection Walk
Natesh Pillai, Aaron Smith
In Diaconis and Saloff-Coste (1996), the authors introduced the simple ``transvection" walk on : at each step, choose two distinct rows and add one to t…
Convergence Rates of Ordering, Testing and Estimation Procedures for Graphons With Fast Boundary Decay Rates
Jeannette Janssen, Na Lin, Aaron Smith
In latent-position random graph models (LPMs), latent vertex positions are sampled from some distribution on a latent space , then edges of an observed grap…
Kac's walk on rotation matrices mixes in steps
Natesh S. Pillai, Aaron Smith
Kac's walk on the rotation group, introduced by Hastings in 1970, is an important high-dimensional Markov chain with applications in statistical physics, statistics, cryptography,…
Variance estimation after matching or re-weighting
Xiang Meng, Aaron Smith, Luke Miratrix
This paper develops a variance estimation framework for matching estimators that enables valid population inference for treatment effects. We provide theoretical analysis of a vari…
No Free Lunch for Stochastic Gradient Langevin Dynamics
Natesh S. Pillai, Aaron Smith, Azeem Zaman
As sample sizes grow, scalability has become a central concern in the development of Markov chain Monte Carlo (MCMC) methods. One general approach to this problem, exemplified by t…