144 citations · 199 across the 7 of their papers we have counts for
4 papers · 1 filter
Augmented Inverse Hybrid Weighting: Robust Inference under Deterministic and Random Distribution Shifts
Ying Jin, Dominik Rothenhäusler
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 str…
Everywhere Valid Bounds on False Discovery Proportions in Conformal Inference
Ziang Song, Ying Jin, Emmanuel J. Candès
Modern applications of conformal inference to multiple testing problems, such as outlier detection and candidate selection, often involve selecting test samples whose conformal p-v…
Model-free selective inference under covariate shift via weighted conformal p-values
Ying Jin, Emmanuel J. Candès
This paper introduces novel weighted conformal p-values and methods for model-free selective inference. The problem is as follows: given test units with covariates and missing…
Bayesian Symbolic Regression
Ying Jin, Weilin Fu, Jian Kang +2
Interpretability is crucial for machine learning in many scenarios such as quantitative finance, banking, healthcare, etc. Symbolic regression (SR) is a classic interpretable machi…