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/

Zendy Plus

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

Zendy Tools

Zendy Open

We discuss the thought-provoking new objective functions for policy learningthat were proposed in "More efficient policy learning via optimal retargeting"by Nathan Kallus and "Learning optimal distributionally robust individualizedtreatment rules" by Weibin Mo, Zhengling Qi, and Yufeng Liu. We show that it isimportant to take the curvature of the value function into account when workingwithin the retargeting framework, and we introduce two ways to do so. We alsodescribe more efficient approaches for leveraging calibration data whenlearning distributionally robust policies.

Discussion of Kallus (2020) and Mo, Qi, and Liu (2020): New Objectives for Policy Learning