4 papers
Statistical Guarantees for Covariance Estimation with Adversarial Corruption under Constraints
Samuel Ozminkowski, Hongmei Jiang, Matey Neykov
We obtain a near-minimax rate on covariance estimation of adversarially corrupted Gaussian data in Frobenius norm when the covariance estimation is assumed to lie in a star-shaped…
Dynamic Co-Expression Network Estimation via Multivariate Mixed-Effects Models
Samuel Ozminkowski, Lifang Hou, David R Jacobs +1
High-throughput sequencing technologies have enabled the collection of large-scale longitudinal -omics data, providing new opportunities for studying co-expression networks among m…
BioKlustering: a web app for semi-supervised learning of maximally imbalanced genomic data
Samuel Ozminkowski, Yuke Wu, Hailey Bruzzone +6
Summary: Accurate phenotype prediction from genomic sequences is a highly coveted task in biological and medical research. While machine-learning holds the key to accurate predicti…
Identifying microbial drivers in biological phenotypes with a Bayesian Network Regression model
Samuel Ozminkowski, Claudia Solis-Lemus
1. In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify reg…