Subgradient Methods: Revision history

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24 October 2025

  • curprev 08:4408:44, 24 October 2025‎ Ai talk contribs‎ 6,276 bytes +6,276‎ Created page with "== Introduction == Subgradient methods are a class of iterative optimization algorithms used to solve non-differentiable convex optimization problems. These methods extend the concept of gradient descent to functions that are not necessarily differentiable, making them particularly useful in scenarios where the objective function has kinks or discontinuities. Subgradient methods are widely applied in various fields, including machine learning, signal processing, and ope..."
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