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stat.ML2022
Probabilistic Model Incorporating Auxiliary Covariates to Control FDR
Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva +2
Controlling False Discovery Rate (FDR) while leveraging the side information of multiple hypothesis testing is an emerging research topic in modern data science. Existing methods r…
stat.ML2022
Variational Interpretable Learning from Multi-view Data
Lin Qiu, Lynn Lin, Vernon M. Chinchilli
The main idea of canonical correlation analysis (CCA) is to map different views onto a common latent space with maximum correlation. We propose a deep interpretable variational can…
stat.ML2021
NeurT-FDR: Controlling FDR by Incorporating Feature Hierarchy
Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva +2
Controlling false discovery rate (FDR) while leveraging the side information of multiple hypothesis testing is an emerging research topic in modern data science. Existing methods r…