We investigate the problem of compound estimation of normal means while
...
The allocation of limited resources to a large number of potential candi...
The uncertainty quantification and error control of classifiers are cruc...
This paper develops novel conformal methods to test whether a new observ...
Transfer learning has enjoyed increasing popularity in a range of big da...
In sparse large-scale testing problems where the false discovery proport...
Adaptive multiple testing with covariates is an important research direc...
We consider the problem of simultaneous estimation of a sequence of depe...
Consider the online testing of a stream of hypotheses where a real–time
...
The simultaneous estimation of many parameters η_i, based on a
correspon...
We develop a new class of distribution–free multiple testing rules for f...
We develop a Nonparametric Empirical Bayes (NEB) framework for compound
...
Standardization has been a widely adopted practice in multiple testing, ...
The article considers the problem of estimating a high-dimensional spars...