all InfoSec news
Disentangle Estimation of Causal Effects from Cross-Silo Data. (arXiv:2401.02154v1 [cs.LG])
cs.CR updates on arXiv.org arxiv.org
Estimating causal effects among different events is of great importance to
critical fields such as drug development. Nevertheless, the data features
associated with events may be distributed across various silos and remain
private within respective parties, impeding direct information exchange between
them. This, in turn, can result in biased estimations of local causal effects,
which rely on the characteristics of only a subset of the covariates. To tackle
this challenge, we introduce an innovative disentangle architecture designed to
facilitate the …
critical data development distributed drug drug development events exchange features great information may private result silos turn