High Performance Computing Framework for Variable Selection on Genome-wide Association Studies
A high-performance computing framework for variable selection in GWAS that integrates state-of-the-art methods and employs novel optimization strategies for efficient processing of high-dimensional data with sparse characteristics.
Dec 3, 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
A novel one-shot federated learning method that performs layer-wise posterior aggregation, achieving superior performance by aggregating posterior distributions instead of point estimates.
Jan 1, 2024