BAYESIAN EMPIRICAL LIKELIHOOD FOR ULTRA-HIGH DIMENSIONAL VARIABLE SELECTION WITH APPLICATION TO DRUG SENSITIVITY
Predicting drug sensitivity and selecting informative biomarkers are fundamental challenges in precision oncology. These tasks are complicated by the ultra-high dimensional nature of omics data, where the number of covariates p far exceeds the sample size n. While variable selection methods are widely used, traditional...