A nonlinear conjugate gradient method with complexity guarantees and its application to nonconvex regression
Nonlinear conjugate gradients are among the most popular techniques for solving continuous optimization problems. Although these schemes have long been studied from a global convergence standpoint, their worst-case complexity properties have yet to be fully understood, especially in the nonconvex se...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-01-01
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| Series: | EURO Journal on Computational Optimization |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S219244062200020X |