Mathematical Optimization for Data Science Group, Saarland University

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Mathematical Optimization for Data Science Group

Department of Mathematics and Computer Science, Saarland University, Germany

Bibliography

[AABR02] F. Alvarez, H. Attouch, J. Bolte, P. Redont: A second-order gradient-like dissipative dynamical system with Hessian-driven damping.: Application to optimization and mechanics. Journal de Mathématiques Pures et Appliquées 81(8):747-779, 2002.

[ACFR23] H. Attouch, Z. Chbani, J. Fadili, H. Riahi: Convergence of iterates for first-order optimization algorithms with inertia and {H}essian driven damping. Optimization 72:1199-1238, 2023.

[ABN23] H. Attouch, R.I. Bot, D-K. Nguyen: Fast convex optimization via time scale and averaging of the steepest descent. ArXiv:2208.08260, 2022.

[AFK23] H. Attouch, J. Fadili, V. Kungurtsev: On the effect of perturbations in first-order optimization methods with inertia and Hessian driven damping. Evolution Equations and Control 12(1):71-117, 2023.

[ALP21] C. Alecsa, S. László, T. Pinţa: An Extension of the Second Order Dynamical System that Models Nesterov’s Convex Gradient Method. Applied Mathematics and Optimization 84:1687-1716, 2021.

[Brezis83] H. Brézis: Opérateurs maximaux monotones et semi-groupes de contractions dans les espace Hilbert. North-Holland Mathematics Studies 5:1-183, 1973.

[SBC15] W. Su, S. Boyd, E.J. Candès: A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights. Journal of Machine Learning Research 17(153):1-43, 2016.

[Nesterov 83] Y. Nesterov: A method for solving the convex programming problem with convergence rate O(1/k^2). Proceedings of the USSR Academy of Sciences, Mathematics, 1983.