Research
Uncertainty Quantification
Doubly Robust Calibration of Prediction Sets under Covariate Shift, Yachong Yang, Arun Kumar Kuchibhotla, Eric Tchetgen Tchetgen
Invited discusssant at International Selection Inference Seminar (Recording) (slides), comparing the ensembling method of Jackknife+ after bootstrap with EFCP (Efficiency first conformal prediction).
Finite-sample Efficient Conformal Prediction (slides) (poster), Yachong Yang, Arun Kumar Kuchibhotla, 2021, ICML.
We consider the problem of obtaining the smallest conformal prediction region given a family of machine learning algorithms and provide two general-purpose selection algorithms and consider coverage as well as width properties of the final prediction region.
Accepted for presentation at CMStatistics.
Finite-sample Efficient Conformal Prediction, Yachong Yang, Arun Kumar Kuchibhotla
High dimensional statistics
The Price of Competition: Effect Size Heterogeneity Matters in High Dimensions, Hua Wang, Yachong Yang and Weijie Su, 2020, preprint.
We introduce a new notion called effect size heterogeneity and prove that the false and true positive rates achieve the optimal trade-off uniformly along the Lasso path when this measure is maximal. Moreover, we demonstrate that the first false selection occurs much earlier when effect size heterogeneity is minimal than when it is maximal.
The Complete Lasso Tradeoff Diagram, Hua Wang, Yachong Yang, Zhiqi Bu and Weijie Su, 2020, NIPS.
Post Selection Inference, Qin Yu, Yang Li, Yumeng Wang, Yachong Yang, Zemin Zheng, 2018, Communications in Statistics - Theory and Methods.
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