96 citations · 270 across the 30 of their papers we have counts for
34 papers
Understanding Linchpin Variables in Markov Chain Monte Carlo
Dootika Vats, Felipe Acosta, Mark L. Huber +1
An introduction to the use of linchpin variables in Markov chain Monte Carlo (MCMC) is provided. Before the widespread adoption of MCMC methods, conditional sampling using linchpin…
Tight relative estimation in the mean of Bernoulli random variables
Mark Huber
Given a stream of Bernoulli random variables, consider the problem of estimating the mean of the random variable within a specified relative error with a specified probability of f…
Tail inequalities for restricted classes of discrete random variables
Mark Huber
Let be an integrable discrete random variable over with for all . Then for any integer , $\mat…
Generating from the Strauss Process using stitching
Mark Huber
The STrauss process is a point process with unnormalized density with respect to a Poisson point process, where each pair of points within a specified distance of each other co…
Fewer colors for perfect simulation of proper colorings
Mark Huber
Given a graph and color set , a is an assignment of a color to each vertex of such that no two vertices connected by an edge ar…
Robust estimation of the mean with bounded relative standard deviation
Mark Huber
Many randomized approximation algorithms operate by giving a procedure for simulating a random variable which has mean equal to the target answer, and a relative standard d…