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The Heavy-Tail Phenomenon in SGD., , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 3964-3975. PMLR, (2021)Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 28578-28597. PMLR, (2023)Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares., , , , и . ALT, том 201 из Proceedings of Machine Learning Research, стр. 1292-1342. PMLR, (2023)Operational Risk Management: A Stochastic Control Framework with Preventive and Corrective Controls., , и . Oper. Res., 68 (6): 1804-1825 (2020)Functional central limit theorems for stationary Hawkes processes and application to infinite-server queues., и . Queueing Syst. Theory Appl., 90 (1-2): 161-206 (2018)Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms., , , , , и . NeurIPS, стр. 18774-18788. (2021)Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance., , , , и . NeurIPS, стр. 18866-18877. (2021)Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks., , , , и . J. Mach. Learn. Res., (2022)Small-noise limit of the quasi-Gaussian log-normal HJM model., и . Oper. Res. Lett., 45 (1): 6-11 (2017)Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 891-901. PMLR, (2019)