# Approximating the diagonal of a Hessian: which sample set of points should be used

arXiv: https://arxiv.org/abs/2104.11821 · HTML: https://mlsanity.com/paper/2104.11821/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Fuzzy hyperparameters update in a second order optimization](https://mlsanity.com/paper/2403.15416/) (2024)

## Abstract (arXiv)

An explicit formula to approximate the diagonal entries of the Hessian is introduced. When the derivative-free technique called generalized centered simplex gradient is used to approximate the gradient, then the formula can be computed for only one additional function evaluation. An error bound is introduced and provides information on the form of the sample set of points that should be used to approximate the diagonal of a Hessian. If the sample set of points is built in a specific manner, it is shown that the technique is O(DeltaS2) accurate approximation of the diagonal entries of the Hessian where DeltaS is the radius of the sample set.