Self-scaling refers to a property of optimization algorithms where the method automatically adjusts its scaling to ensure better convergence behavior. This feature is especially useful in situations where the problem's landscape may exhibit varying levels of curvature, allowing for more efficient searching for optimal solutions without manual intervention.
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