159 citations · 197 across the 10 of their papers we have counts for
9 papers · 1 filter
Rapid mixing of a Markov chain for an exponentially weighted aggregation estimator
David Pollard, Dana Yang
The Metropolis-Hastings method is often used to construct a Markov chain with a given as its stationary distribution. The method works even if is known only up to an intrac…
Fair quantile regression
Dana Yang, John Lafferty, David Pollard
Quantile regression is a tool for learning conditional distributions. In this paper we study quantile regression in the setting where a protected attribute is unavailable when fitt…
Remarks on Kneip's linear smoothers
Sören R. Künzel, David Pollard, Dana Yang
We were trying to understand the analysis provided by Kneip (1994, Ordered Linear Smoothers). In particular we wanted to persuade ourselves that his results imply the oracle inequa…
Estimation in Functional Regression for General Exponential Families
Winston Wei Dou, David Pollard, Harrison H. Zhou
This paper studies a class of exponential family models whose canonical parameters are specified as linear functionals of an unknown infinite-dimensional slope function. The optima…
Some thoughts on Le Cam's statistical decision theory
David Pollard
The paper contains some musings about the abstractions introduced by Lucien Le Cam into the asymptotic theory of statistical inference and decision theory. A short, self-contained…
Asymptotics for minimisers of convex processes
Nils Lid Hjort, David Pollard
By means of two simple convexity arguments we are able to develop a general method for proving consistency and asymptotic normality of estimators that are defined by minimisation o…