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@jemoka / Jemoka Knowledge Base / raw/concept/kbhnon_linear_optimization.md
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--- title: "non-linear optimization" source: https://www.jemoka.com/posts/kbhnon_linear_optimization/ --- Traditional techniques for non-convex problems involve compromises. local optimization: find a point that minimize \(f_{0}\) among feasible points near it; can handle large problems (i.e. neural networks); algorithm parameter tuning. global optimization methods: basically just cast it into a convex optimization problem.