---
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.
