Function gradientDescent

This file is the main entry point for the numopt-js library.

Role in system:

Exports all public API functions and types
Provides clean, focused interface for users
Single import point for the entire library

For first-time readers:

Import everything you need from this file
Check individual algorithm files for detailed documentation
All algorithms follow consistent patterns

gradientDescent(
    initialParameters: Float64Array,
    costFunction: CostFn,
    gradientFunction: GradientFn,
    options?: GradientDescentOptions,
): GradientDescentResult
Performs gradient descent optimization to minimize a cost function.

Algorithm:
1. Start with initial parameters
2. Compute gradient at current point
3. Move in negative gradient direction (steepest descent)
4. Use line search or fixed step size to determine step
5. Repeat until convergence or max iterations
Convergence criteria:
- Gradient norm < tolerance
- Step size < tolerance
- Maximum iterations reached
Parameters
- initialParameters: Float64Array
- costFunction: CostFn
- gradientFunction: GradientFn
- options: GradientDescentOptions = {}
Returns GradientDescentResult
- Defined in core/gradientDescent.ts:275