3 papers
stat.ML2020
Model updating after interventions paradoxically introduces bias
James Liley, Samuel R Emerson, Bilal A Mateen +3
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Rece…
cs.CR2019
Design choices for productive, secure, data-intensive research at scale in the cloud
Diego Arenas, Jon Atkins, Claire Austin +22
We present a policy and process framework for secure environments for productive data science research projects at scale, by combining prevailing data security threat and risk prof…
stat.ME2018
Shrinkage estimation of large covariance matrices using multiple shrinkage targets
Harry Gray, Gwenaël G. R. Leday, Catalina A. Vallejos +1
Linear shrinkage estimators of a covariance matrix --- defined by a weighted average of the sample covariance matrix and a pre-specified shrinkage target matrix --- are popular whe…