High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

Abstract: Gene expression data usually present the characteristics of high dimension and small sample size. In such data, it is crucial to conduct feature selection to reduce dimensions and retain key ...

Abstract: Subset selection has been widely studied but remains underexplored for synthetic tabular data, particularly in data sharing contexts that require high quality data. While generative models ...