Skip to content

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Sep 2026

Conformal Policy Learning with Distribution-Free Safety Guarantees

Policy learning aims to determine who should be treated based on individual characteristics. In high-stakes settings such as medicine and public policy where safety is a central concern, improving the average outcomes alone may not be sufficient: decision makers may also seek to protect individuals from harm, in line w...

Ying Jin, Naoki Egami · 0 citations
Preprint Aug 2026

Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts

Reweighting source samples to match a target covariate distribution is a standard response to distribution shift when generalizing evidence from one population to another. This strategy is well suited to deterministic, learnable covariate discrepancies, but can be insufficient when source--target population differences...

Ying Jin, Dominik Rothenhäusler · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.