Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits

Grigory Begunov, Alexander Tyurin

In centralized, distributed, and federated learning with stochastic gradients and $n$ workers, it was recently shown that it is infeasible to find an $\epsilon$-stationary point…