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Sketched Calibration for Conformal Prediction under Covariate Shift
Mehrdad Pournaderi
Weighted conformal prediction corrects for covariate shift by reweighting calibration scores with the likelihood ratio between target and source covariates. Its cost grows with the…
Calibrated Order-Randomized Rosenblatt Tests
Mehrdad Pournaderi
We test whether a multivariate vector X conforms to a specified distribution F, as in copula modelling and density forecasting. The Rosenblatt transform reduces this to testing uni…
Finite-Sample FDR Control for Greedy Aggregation over Networks
Mehrdad Pournaderi
Distributed multiple testing asks sites, each holding p-values for its own hypotheses, to control the false discovery rate (FDR) of the discoveries made across the whole networ…
Communication-Efficient Distribution-Free Inference Over Networks
Mehrdad Pournaderi, Yu Xiang
Consider a star network where each local node possesses a set of test statistics that exhibit a symmetric distribution around zero when their corresponding null hypothesis is true.…
On Large-Scale Multiple Testing Over Networks: An Asymptotic Approach
Mehrdad Pournaderi, Yu Xiang
This work concerns developing communication- and computation-efficient methods for large-scale multiple testing over networks, which is of interest to many practical applications.…
Communication-Efficient Distributed Multiple Testing for Large-Scale Inference
Mehrdad Pournaderi, Yu Xiang
The Benjamini-Hochberg (BH) procedure is a celebrated method for multiple testing with false discovery rate (FDR) control. In this paper, we consider large-scale distributed networ…