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Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework., , , , , and . CoRR, (2020)Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 10997-11057. PMLR, (2022)On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit., , , , and . ACSCC, page 1013-1017. IEEE, (2021)Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity., , , , and . CoRR, (2019)On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit., , , , and . CoRR, (2020)Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation., , , and . CoRR, (2023)High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise., , , , , and . CoRR, (2023)Correlation Aware Sparsified Mean Estimation Using Random Projection., , and . CoRR, (2023)On noise-enhanced distributed inference in the presence of Byzantines., , , , , , and . Allerton, page 1222-1229. IEEE, (2011)Model Sparsity Can Simplify Machine Unlearning., , , , , , , and . NeurIPS, (2023)