3 papers
stat.ML2026
On the Adversarial Robustness of Learning-based Conformal Novelty Detection
Daofu Zhang, Mehrdad Pournaderi, Hanne M. Clifford +2
This paper studies the adversarial robustness of conformal novelty detection. In particular, we focus on two powerful learning-based frameworks that come with finite-sample false d…
stat.ML2026
Training-Conditional Coverage Bounds under Covariate Shift
Mehrdad Pournaderi, Yu Xiang
Conformal prediction methodology has recently been extended to the covariate shift setting, where the distribution of covariates differs between training and test data. While exist…
eess.SP2025
Distributed Multiple Testing with False Discovery Rate Control in the Presence of Byzantines
Daofu Zhang, Mehrdad Pournaderi, Yu Xiang +1
This work studies distributed multiple testing with false discovery rate (FDR) control in the presence of Byzantine attacks, where an adversary captures a fraction of the nodes and…