# On a convergence property of a geometrical algorithm for statistical manifolds

arXiv: https://arxiv.org/abs/1909.12644 · HTML: https://mlsanity.com/paper/1909.12644/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2019.

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

- [Geometry of EM and related iterative algorithms](https://mlsanity.com/paper/2209.01301/) (2022)

## Abstract (arXiv)

In this paper, we examine a geometrical projection algorithm for statistical inference. The algorithm is based on Pythagorean relation and it is derivative-free as well as representation-free that is useful in nonparametric cases. We derive a bound of learning rate to guarantee local convergence. In special cases of m-mixture and e-mixture estimation problems, we calculate specific forms of the bound that can be used easily in practice.