English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In a recent paper, Nguyen, Kuhn, and Esfahani (2018) built a distributionallyrobust estimator for the precision matrix of the Gaussian distribution. Thedistributional uncertainty size is a key ingredient in the construction of thisestimator. We develop a statistical theory which shows how to optimally choosethe uncertainty size to minimize the associated Stein loss. Surprisingly,rather than the expected canonical square-root scaling rate, the optimaluncertainty size scales linearly with the sample size.

Optimal Uncertainty Size in Distributionally Robust Inverse Covariance Estimation