2 papers
math.OC2026
Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits
Grigory Begunov, Alexander Tyurin
In centralized, distributed, and federated learning with stochastic gradients and workers, it was recently shown that it is infeasible to find an -stationary point…
cs.DC2026
Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods
Grigory Begunov, Alexander Tyurin
Modern distributed optimization methods mostly rely on traditional synchronous approaches, despite substantial recent progress in asynchronous optimization. We revisit Synchronous…