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A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning., , , and . J. Mach. Learn. Res., (2020)Stochastic Conditional Gradient++: (Non)Convex Minimization and Continuous Submodular Maximization., , , and . SIAM J. Optim., 30 (4): 3315-3344 (2020)On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms, , and . (Aug 27, 2019)FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization., , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 2021-2031. PMLR, (2020)Distribution-Agnostic Model-Agnostic Meta-Learning., , and . CoRR, (2020)Decentralized double stochastic averaging gradient., and . ACSSC, page 406-410. IEEE, (2015)Doubly stochastic algorithms for large-scale optimization., , and . ACSSC, page 1705-1709. IEEE, (2016)An incremental quasi-Newton method with a local superlinear convergence rate., , and . ICASSP, page 4039-4043. IEEE, (2017)Large-scale nonconvex stochastic optimization by Doubly Stochastic Successive Convex approximation., , , and . ICASSP, page 4701-4705. IEEE, (2017)A Primal-Dual Quasi-Newton Method for Exact Consensus Optimization., , and . IEEE Trans. Signal Process., 67 (23): 5983-5997 (2019)