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Research on Lipschitz continuous concept in Machine Learning part5
- This paper discusses derivative-free smooth optimization problems in machine learning.
- Two novel derivative-free methods are proposed for minimizing functions with Lipschitz continuous gradients.
- The methods use gradient approximations based on adaptive finite differences.
- Numerical experiments demonstrate the advantages of the proposed methods over other existing methods.
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