3 citations · 5 across the 3 of their papers we have counts for
3 papers
stat.ME2026
Parsimonious Subset Selection for Generalized Linear Models with Biomedical Applications
Anant Mathur, Benoit Liquet, Samuel Muller +1
High-dimensional biomedical studies require models that are simultaneously accurate, sparse, and interpretable, yet exact best subset selection for generalized linear models is com…
stat.ME2024★ 3 cited
Air-HOLP: Adaptive Regularized Feature Screening for High Dimensional Correlated Data
Ibrahim Joudah, Samuel Muller, Houying Zhu
Handling high-dimensional datasets presents substantial computational challenges, particularly when the number of features far exceeds the number of observations and when features…
stat.ME2022★ 2 cited
COMBSS: Best Subset Selection via Continuous Optimization
Sarat Moka, Benoit Liquet, Houying Zhu +1
The problem of best subset selection in linear regression is considered with the aim to find a fixed size subset of features that best fits the response. This is particularly chall…