# HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step

arXiv: https://arxiv.org/abs/1610.04329 · HTML: https://mlsanity.com/paper/1610.04329/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Oct 2016.

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

- [Online Deep Learning from Doubly-Streaming Data](https://mlsanity.com/paper/2204.11793/) (2022)

## Abstract (arXiv)

In this article, we develop and analyze a homotopy continuation method, referred to as HONES , for solving the sequential generalized projections in Online Newton Step, as well as the generalized problem known as sequential standard quadratic programming. HONES is fast, tuning-free, error-free (up to machine error) and adaptive to the solution sparsity. This is confirmed by both careful theoretical analysis and extensive experiments on both synthetic and real data.