Julian Späth

The paper introduces dsMTL, a framework for privacy-preserving, distributed multi-task machine learning, and evaluates its performance in identifying biological signatures across distributed datasets.

sPLINK enables federated GWAS on distributed datasets without data sharing, preserving privacy and accuracy while being robust to heterogeneity.