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Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations.

, , , , , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 242-299. PMLR, (2020)

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On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions., , , and . CoRR, (2020)Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations., , , , , and . COLT, volume 125 of Proceedings of Machine Learning Research, page 242-299. PMLR, (2020)On Lower and Upper Bounds in Smooth and Strongly Convex Optimization., , and . J. Mach. Learn. Res., (2016)Hidden Minima in Two-Layer ReLU Networks.. CoRR, (2023)Oracle complexity of second-order methods for smooth convex optimization., , and . Math. Program., 178 (1-2): 327-360 (2019)Spurious Local Minima of Shallow ReLU Networks Conform with the Symmetry of the Target Model., and . CoRR, (2019)Limitations on Variance-Reduction and Acceleration Schemes for Finite Sum Optimization.. CoRR, (2017)Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II., and . NeurIPS, page 15162-15174. (2021)Oracle Complexity of Second-Order Methods for Finite-Sum Problems., and . ICML, volume 70 of Proceedings of Machine Learning Research, page 205-213. PMLR, (2017)A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates., , and . ALT, volume 117 of Proceedings of Machine Learning Research, page 111-132. PMLR, (2020)