58 citations · 198 across the 19 of their papers we have counts for
8 papers · 1 filter
Exact Limits of Inference in Coalescent Models
James E. Johndrow, Julia A. Palacios
Recovery of population size history from molecular sequence data is an important problem in population genetics. Inference commonly relies on a coalescent model linking the populat…
Error bounds for Approximations of Markov chains used in Bayesian Sampling
James E. Johndrow, Jonathan C. Mattingly
We give a number of results on approximations of Markov kernels in total variation and Wasserstein norms weighted by a Lyapunov function. The results are applied to examples from B…
A Decision Theoretic Approach to A/B Testing
David Goldberg, James E. Johndrow
A/B testing is ubiquitous within the machine learning and data science operations of internet companies. Generically, the idea is to perform a statistical test of the hypothesis th…
Coupling and Decoupling to bound an approximating Markov Chain
James E. Johndrow, Jonathan C. Mattingly
This simple note lays out a few observations which are well known in many ways but may not have been said in quite this way before. The basic idea is that when comparing two differ…
Bayes Shrinkage at GWAS scale: Convergence and Approximation Theory of a Scalable MCMC Algorithm for the Horseshoe Prior
James E. Johndrow, Paulo Orenstein, Anirban Bhattacharya
The horseshoe prior is frequently employed in Bayesian analysis of high-dimensional models, and has been shown to achieve minimax optimal risk properties when the truth is sparse.…
An algorithm for removing sensitive information: application to race-independent recidivism prediction
James E. Johndrow, Kristian Lum
Predictive modeling is increasingly being employed to assist human decision-makers. One purported advantage of replacing or augmenting human judgment with computer models in high s…