gradient-descent-first-order-negative-gradient

IN premise — entries/2026/06/21/wiki-Gradient_descent-chunk-1.md

Created 2026-06-21T09:55:50+00:00

Gradient descent is a first-order iterative optimization algorithm that moves in the negative gradient direction (steepest descent) to find local minima of differentiable functions

Dependents

These beliefs depend on this one:

• OUT gradient-descent-effective-global-optimizer — Gradient descent with backpropagation effectively finds global optima for neural network training in practice, despite lacking global guarantees.