3 papers
stat.ME2026
PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
Theophilus Quachie Asenso, Zhi Zhao, Maren-Helene Langeland Degnes +3
High-dimensional interaction models are useful for studying, for example, how a large set of variables of interest, such as gene expression or other omics features, interact with a…
stat.ME2024
Integrating Multiple Data Sources with Interactions in Multi-Omics Using Cooperative Learning
Matteo D'Alessandro, Theophilus Quachie Asenso, Manuela Zucknick
Modeling with multi-omics data presents multiple challenges such as the high-dimensionality of the problem (), the presence of interactions between features, and the need…
stat.ME2023
An ADMM approach for multi-response regression with overlapping groups and interaction effects
Theophilus Quachie Asenso, Manuela Zucknick
In this paper, we consider the regularized multi-response regression problem where there exists some structural relation within the responses and also between the covariates and a…