Much of the overhead in prior schemes comes from the fact that they tightly couple coding for all three problems into a single framework.
In fact, we empirically show that the conventional random user selection strategies for federated learning lead to leaking users' individual models within number of rounds linear in the number of users.
We further propose folded Lagrange coded computing, referred to as folded LCC or FLCC, to incorporate the developed techniques into a specific coded computing setting.
In this work, we empirically show that the square function is not the best degree-$2$ polynomial that can replace the ReLU function even when restricting the polynomials to have integer coefficients.
Partial quorum systems are widely used in distributed key-value stores due to their latency benefits at the expense of providing weaker consistency guarantees.