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Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise., , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 8970-8980. PMLR, (2020)Asymptotic normality of extensible grid sampling., и . Stat. Comput., 29 (1): 53-65 (2019)Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations., , , и . CoRR, (2024)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)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)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)