Inertial Newton Algorithms Avoiding Strict Saddle Points
Author:
Funder
European Research Council
Air Force Office of Scientific Research
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Management Science and Operations Research,Control and Optimization
Link
https://link.springer.com/content/pdf/10.1007/s10957-023-02330-0.pdf
Reference49 articles.
1. Alecsa, Cristian Daniel, László, Szilárd Csaba., Viorel, Adrian: A gradient-type algorithm with backward inertial steps associated to a nonconvex minimization problem. Numer. Algor. 84(2), 485–512 (2020)
2. Alecsa, Cristian Daniel, László, Szilárd Csaba., Pinţa, Titus: An extension of the second order dynamical system that models Nesterov’s convex gradient method. Appl. Math. Optim. 84(2), 1687–1716 (2021)
3. Alvarez, Felipe, Attouch, Hedy, Bolte, Jérôme., Redont, Patrick: 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)
4. Ašić, M.D., Adamović, D.D.: Limit points of sequences in metric spaces. Am. Math. Monthly 77(6), 613–616 (1970). https://www.tandfonline.com/doi/abs/10.1080/00029890.1970.11992549
5. Attouch, H., László, S.C.: Newton-like inertial dynamics and proximal algorithms governed by maximally monotone operators. SIAM J. Optim. 30(4), 3252–3283 (2020)
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