Privacy of federated QR decomposition using additive secure multiparty computation. (arXiv:2210.06163v1 [cs.CR])

Federated learning (FL) is a privacy-aware data mining strategy keeping the
private data on the owners' machine and thereby confidential. The clients
compute local models and send them to an aggregator which computes a global
model. In hybrid FL, the local parameters are additionally masked using secure
aggregation, such that only the global aggregated statistics become available
in clear text, not the client specific updates. Federated QR decomposition has
not been studied extensively in the context of cross-silo federated learning. …

arxiv computation privacy