Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
Abstract: Robust tensor variational methods based on CANDECOMP/PARAFAC (CP) decomposition have attracted significant interest for efficiently exploiting high-dimensional multipath channel data, ...
Patients were stratified to cohort A (unspecified tumors) or cohort B (rare genomic alterations). The TARGET-CRM design permits cohort B patients to immediately enroll at one dose level below the ...
Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...
This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including ...
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