MF mechanism consistently performs at least as well as the best prior methods.

Motivated by the above findings, we propose FedCCFA, a federated learning framework with classifier clustering and feature alignment.

In our work, we propose the first distributed method with client sampling and provable tolerance to Byzantine workers.

Local treatment effects are a common quantity found throughout the empirical sciences that measure the treatment effect among those who comply with what they are assigned. Most of the literature is focused on estimating the average of such quantity, which is called the " local average treatment effect (LATE) " [

The objective(1) can be extended to a weighted average, but we do not write out the weights and consider them as part ofℓn(x,ξ)andFn(x).