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GradientDescentOptimizer

oxilean_std::numerical_analysis::types

Struct GradientDescentOptimizer 

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pub struct GradientDescentOptimizer {
    pub learning_rate: f64,
    pub tol: f64,
    pub max_iter: u32,
}
Expand description

Gradient-descent minimizer for a smooth function f : Rⁿ → R.

Uses fixed step size (learning rate) with optional Armijo line-search.

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§learning_rate: f64§tol: f64§max_iter: u32

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impl GradientDescentOptimizer

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pub fn new(learning_rate: f64, tol: f64, max_iter: u32) -> Self

Create a new optimizer.

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pub fn minimize( &self, grad: &dyn Fn(&[f64]) -> Vec<f64>, x0: &[f64], ) -> (Vec<f64>, u32, bool)

Minimize f starting from x0 using grad to supply ∇f.

Returns (minimizer, num_iters, converged).

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