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Exact and Armijo rates on an anisotropic quadratic
Example
For , the exact-gradient step has an explicit nontrivial line minimizer, and Armijo backtracking shows the accepted-step bound in a finite calculation.
Facts & Assumptions
Given: on , initial point , exact gradient line search, and Armijo parameters , .
Exact gradient line search has a global objective-gap contraction: under compact sublevel and , an exact negative-gradient line-search step contracts the objective gap by at least the factor .
Armijo gradient descent has an explicit global linear rate: with and , the accepted step is at least and the objective-gap factor is .
Gradient descent: backtracking tests and accepts when .
Heine-Borel in : with the Euclidean metric a subset of is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line: in Euclidean space, a closed and bounded set is compact.
Verification
The Hessian is , so and ; is the unique minimizer and . The sublevel set is closed by continuity and bounded because and on it; it is compact by [F4]. The gradient at is .
Along the negative-gradient ray, and , so the unique minimizer is . It gives and . The theorem [F1] bounds the gap by , and .
For Armijo, the first trial has candidate with value and threshold , so it fails. The second trial has candidate with value and threshold , so it fails. At , the candidate is with value , the Armijo threshold; hence [F3] accepts .
Here , so [F2] gives the gap factor . The actual new gap is below . The exact and Armijo calculations concern objective gaps; neither calculation supplies an iterate-error bound.
Depends on
- Gradient descent
- The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case
- Heine-Borel in $\mathbb{R}^n$: with the Euclidean metric a subset of $\mathbb{R}^n$ is compact if and only if it is closed and bounded, and the proof by bisection uses no choice principle; the same holds on the real line
- Exact gradient line search has a global objective-gap contraction
- Armijo gradient descent has an explicit global linear rate
Used by
Nothing in the library uses this result yet.
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