253 citations · 589 across the 13 of their papers we have counts for
13 papers
Ranking and Selection in Large-Scale Inference of Heteroscedastic Units
Bowen Gang, Luella Fu, Gareth James +1
The allocation of limited resources to a large number of potential candidates presents a pervasive challenge. In the context of ranking and selecting top candidates from heterosced…
Asymmetric error control under imperfect supervision: a label-noise-adjusted Neyman-Pearson umbrella algorithm
Shunan Yao, Bradley Rava, Xin Tong +1
Label noise in data has long been an important problem in supervised learning applications as it affects the effectiveness of many widely used classification methods. Recently, imp…
A Burden Shared is a Burden Halved: A Fairness-Adjusted Approach to Classification
Bradley Rava, Wenguang Sun, Gareth M. James +1
We investigate the fairness issue in classification, where automated decisions are made for individuals from different protected groups. In high-consequence scenarios, decision err…
Nonparametric Empirical Bayes Estimation on Heterogeneous Data
Trambak Banerjee, Luella J. Fu, Gareth M. James +2
The simultaneous estimation of many parameters based on data collected from corresponding studies is a key research problem that has received renewed attention in the high-dimensio…
Irrational Exuberance: Correcting Bias in Probability Estimates
Gareth M. James, Peter Radchenko, Bradley Rava
We consider the common setting where one observes probability estimates for a large number of events, such as default risks for numerous bonds. Unfortunately, even with unbiased es…
Heterocedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing
Luella Fu, Bowen Gang, Gareth M. James +1
Standardization has been a widely adopted practice in multiple testing, for it takes into account the variability in sampling and makes the test statistics comparable across differ…