# SelfieBoost: A Boosting Algorithm for Deep Learning

arXiv: https://arxiv.org/abs/1411.3436 · HTML: https://mlsanity.com/paper/1411.3436/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2014.

## Built on by (most cited first, 2 of 2)

- [ReconBoost: Boosting Can Achieve Modality Reconcilement](https://mlsanity.com/paper/2405.09321/) (2024)
- [Multiple Additive Neural Networks for Structured and Unstructured Data](https://mlsanity.com/paper/2604.26888/) (2026)

## Abstract (arXiv)

We describe and analyze a new boosting algorithm for deep learning called SelfieBoost. Unlike other boosting algorithms, like AdaBoost, which construct ensembles of classifiers, SelfieBoost boosts the accuracy of a single network. We prove a log(1/ε) convergence rate for SelfieBoost under some "SGD success" assumption which seems to hold in practice.