Leveraging family data to design Mendelian Randomization that is provably robust to population stratification.
Sign Up to like & getrecommendations! Published in 2023 at "Genome research"
DOI: 10.1101/gr.277664.123
Abstract: Mendelian Randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases due to… read more here.
Keywords: provably robust; mendelian randomization; family data; population ... See more keywords
Training Provably Robust Models by Polyhedral Envelope Regularization.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3111892
Abstract: Training certifiable neural networks enables us to obtain models with robustness guarantees against adversarial attacks. In this work, we introduce a framework to obtain a provable adversarial-free region in the neighborhood of the input data… read more here.
Keywords: polyhedral envelope; robust models; training provably; envelope regularization ... See more keywords