The multi-class Stackelberg prediction game with least squares loss-Reference-Cited by-同舟云学术

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The multi-class Stackelberg prediction game with least squares loss

Published:2024-08-31 Issue: Volume: Page:
ISSN:1389-4420
Container-title:Optimization and Engineering
language:en
Short-container-title:Optim Eng

Author:

Han Shanheng,Lin Yangjun,Wang Jiaxin,Zhang Lei-Hong

Funder

National Natural Science Foundation of China

Jiangsu Shuangchuang Project

Academic Degree and Postgraduate Education Reform Project of Jiangsu Province

China Association of Higher Education

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11081-024-09921-4.pdf

Reference39 articles.

1. Absil P-A, Baker CG, Gallivan KA (2007) Trust-region methods on Riemannian manifolds. Found Comput Math 7:303–330

2. Absil P-A, Mahony R, Sepulchre R (2008) Optimization algorithms on matrix manifolds. Princeton University Press, Princeton

3. Bai Z, Lu D, Vandereycken B (2018) Robust Rayleigh quotient minimization and nonlinear eigenvalue problems. SIAM J Sci Comput 40:A3495–A3522

4. Bai Z, Li R-C, Lu D (2022) Sharp estimation of convergence rate for self-consistent field iteration to solve eigenvector-dependent nonlinear eigenvalue problems. SIAM J Matrix Anal Appl 43:301–327

5. Bishop N, Tran-Thanh L, Gerding EH (2020) Optimal learning from verified training data. Adv Neural Inf Process Syst 33:9520–9529

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