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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…
math.OC2025
Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics
Alexander Tyurin
In distributed stochastic optimization, where parallel and asynchronous methods are employed, we establish optimal time complexities under virtually any computation behavior of wor…