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Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework., , , , , and . CoRR, (2020)On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit., , , , and . ACSCC, page 1013-1017. IEEE, (2021)Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 10997-11057. PMLR, (2022)On Decentralized Self-localization and Tracking Under Measurement Origin Uncertainty., , , and . FUSION, page 1-8. IEEE, (2019)Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations., , , , and . IEEE Trans. Signal Inf. Process. over Networks, (2021)Fedvarp: Tackling the variance due to partial client participation in federated learning., , , and . UAI, volume 180 of Proceedings of Machine Learning Research, page 906-916. PMLR, (2022)STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning., , , , , , and . NeurIPS, page 6050-6061. (2021)What Is Missing in IRM Training and Evaluation? Challenges and Solutions., , , , , and . ICLR, OpenReview.net, (2023)Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity., , , , and . CoRR, (2019)High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise., , , , , and . CoRR, (2023)