An adaptive regularized proximal Newton-type methods for composite optimization over the Stiefel manifold
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10589-024-00595-3.pdf
Reference36 articles.
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2. Absil, P.-A., Malick, J.: Projection-like retractions on matrix manifolds. SIAM J. Optim. 22(1), 135–158 (2012). https://doi.org/10.1137/100802529
3. Absil, P.-A., Mahony, R., Sepulchre, R.: Optimization algorithms on matrix manifolds. Princeton University Press, Princeton (2008)
4. Aravkin, A.Y., Baraldi, R., Orban, D.: A proximal quasi-Newton trust-region method for nonsmooth regularized optimization. SIAM J. Optim. 32(2), 900–929 (2022). https://doi.org/10.1137/21M1409536
5. Borckmans, P.B., Easter Selvan, S., Boumal, N., Absil, P.-A.: A Riemannian subgradient algorithm for economic dispatch with valve-point effect. J. Comput. Appl. Math. 255, 848–866 (2014). https://doi.org/10.1016/j.cam.2013.07.002
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