5 citations · 20 across the 16 of their papers we have counts for
18 papers
Markov Chain CLTs: Resolving Open Problems
Austin Brown, Jeffrey S. Rosenthal, Quan Zhou
Markov chain central limit theorems (CLTs) and their associated variances are very important for implementing Markov chain Monte Carlo algorithms among other applications. Häggströ…
Fast Replica Exchange Stochastic Gradient Langevin Dynamics
Guanxun Li, Guang Lin, Zecheng Zhang +1
Application of the replica exchange (i.e., parallel tempering) technique to Langevin Monte Carlo algorithms, especially stochastic gradient Langevin dynamics (SGLD), has scored gre…
A quickest detection problem with false negatives
Tiziano De Angelis, Jhanvi Garg, Quan Zhou
We formulate and solve a variant of the quickest detection problem which features false negatives. A standard Brownian motion acquires a drift at an independent exponential random…
Fairness in Forecasting of Observations of Linear Dynamical Systems
Quan Zhou, Jakub Marecek, Robert N. Shorten
In machine learning, training data often capture the behaviour of multiple subgroups of some underlying human population. This behaviour can often be modelled as observations of an…
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems
Hyunwoong Chang, Changwoo J. Lee, Zhao Tang Luo +2
The multiple-try Metropolis (MTM) algorithm is an extension of the Metropolis-Hastings (MH) algorithm by selecting the proposed state among multiple trials according to some weight…
Bayesian Multi-task Variable Selection with an Application to Differential DAG Analysis
Guanxun Li, Quan Zhou
In this paper, we study the Bayesian multi-task variable selection problem, where the goal is to select activated variables for multiple related data sets simultaneously. Our propo…
Order-based Structure Learning without Score Equivalence
Hyunwoong Chang, James Cai, Quan Zhou
We propose an empirical Bayes formulation of the structure learning problem, where the prior specification assumes that all node variables have the same error variance, an assumpti…
Rapid Convergence of Informed Importance Tempering
Quan Zhou, Aaron Smith
Informed Markov chain Monte Carlo (MCMC) methods have been proposed as scalable solutions to Bayesian posterior computation on high-dimensional discrete state spaces, but theoretic…
Dimension-free Mixing for High-dimensional Bayesian Variable Selection
Quan Zhou, Jun Yang, Dootika Vats +2
Yang et al. (2016) proved that the symmetric random walk Metropolis--Hastings algorithm for Bayesian variable selection is rapidly mixing under mild high-dimensional assumptions. W…
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes
Quan Zhou, Hyunwoong Chang
Structure learning via MCMC sampling is known to be very challenging because of the enormous search space and the existence of Markov equivalent DAGs. Theoretical results on the mi…
A hypothesis-testing perspective on the G-normal distribution theory
Shige Peng, Quan Zhou
The G-normal distribution was introduced by Peng [2007] as the limiting distribution in the central limit theorem for sublinear expectation spaces. Equivalently, it can be interpre…
Yule's "nonsense correlation" solved: Part II
Philip A. Ernst, L. C. G. Rogers, Quan Zhou
In 1926, G. Udny Yule considered the following: given a sequence of pairs of random variables (), and letting and where $S…
Optimal real-time detection of a drifting Brownian coordinate
Philip Ernst, Goran Peskir, Quan Zhou
Consider the motion of a Brownian particle in three dimensions, whose two spatial coordinates are standard Brownian motions with zero drift, and the remaining (unknown) spatial coo…
When is it best to follow the leader?
Philip Ernst, L. C. G. Rogers, Quan Zhou
An object is hidden in one of boxes. Initially, the probability that it is in box is . You then search in continuous time, observing box at time , and rece…
Thick distribution tails in models of cancer secondary tumors
Philip A. Ernst, Marek Kimmel, Monika Kurpas +1
Recent progress in microdissection and in DNA sequencing has enabled subsampling of multi-focal cancers in organs such as the liver in several hundred spots, helping to determine t…
Asymptotics of multivariate contingency tables with fixed marginals
Quan Zhou
We consider the asymptotic distribution of a cell in a 2 x ... x 2 contingency table as the fixed marginal totals tend to infinity. The asymptotic order of the cell variance is der…
Sequential rerandomization
Quan Zhou, Philip Ernst, Kari Lock Morgan +2
The seminal work of Morgan and Rubin (2012) considers rerandomization for all the units at one time. In practice, however, experimenters may have to rerandomize units sequentially.…
The value of foresight
Philip Ernst, L. C. G. Rogers, Quan Zhou
Suppose you have one unit of stock, currently worth 1, which you must sell before time . The Optional Sampling Theorem tells us that whatever stopping time we choose to sell, th…