Stopping Rules for Gradient Methods for Non-Convex Problems with Additive Noise in Gradient
We study the gradient method under the assumption that an additively inexact gradient is available for, generally speaking, non-convex problems. The non-convexity of the objective function, as well as the use of an inexactness specified gradient at iterations, can lead to various problems. For examp...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
16.05.2022
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Subjects | |
Online Access | Get full text |
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Summary: | We study the gradient method under the assumption that an additively inexact
gradient is available for, generally speaking, non-convex problems. The
non-convexity of the objective function, as well as the use of an inexactness
specified gradient at iterations, can lead to various problems. For example,
the trajectory of the gradient method may be far enough away from the starting
point. On the other hand, the unbounded removal of the trajectory of the
gradient method in the presence of noise can lead to the removal of the
trajectory of the method from the desired exact solution. The results of
investigating the behavior of the trajectory of the gradient method are
obtained under the assumption of the inexactness of the gradient and the
condition of gradient dominance. It is well known that such a condition is
valid for many important non-convex problems. Moreover, it leads to good
complexity guarantees for the gradient method. A rule of early stopping of the
gradient method is proposed. Firstly, it guarantees achieving an acceptable
quality of the exit point of the method in terms of the function. Secondly, the
stopping rule ensures a fairly moderate distance of this point from the chosen
initial position. In addition to the gradient method with a constant step, its
variant with adaptive step size is also investigated in detail, which makes it
possible to apply the developed technique in the case of an unknown Lipschitz
constant for the gradient. Some computational experiments have been carried out
which demonstrate effectiveness of the proposed stopping rule for the
investigated gradient methods. |
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DOI: | 10.48550/arxiv.2205.07544 |