# Optimal AdaBoost Converges

arXiv: https://arxiv.org/abs/2210.07808 · HTML: https://mlsanity.com/paper/2210.07808/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 11 Oct 2022.

## Builds on (most cited first, 2 of 2)

- [Gradient Descent Maximizes the Margin of Homogeneous Neural Networks](https://mlsanity.com/paper/1906.05890/) (2019)
- [Limit Cycles of AdaBoost](https://mlsanity.com/paper/2209.06928/) (2022)

## Abstract (arXiv)

The following work is a preprint collection of formal proofs regarding the convergence properties of the AdaBoost machine learning algorithm's classifier and margins. Various math and computer science papers have been written regarding conjectures and special cases of these convergence properties. Furthermore, the margins of AdaBoost feature prominently in the research surrounding the algorithm. At the zenith of this paper we present how AdaBoost's classifier and margins converge on a value that agrees with decades of research. After this, we show how various quantities associated with the combined classifier converge.