# Online Algorithms for Multiclass Classification using Partial Labels

arXiv: https://arxiv.org/abs/1912.11367 · HTML: https://mlsanity.com/paper/1912.11367/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Dec 2019.

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

- [Multiclass Classification using dilute bandit feedback](https://mlsanity.com/paper/2105.08093/) (2021)

## Abstract (arXiv)

In this paper, we propose online algorithms for multiclass classification using partial labels. We propose two variants of Perceptron called Avg Perceptron and Max Perceptron to deal with the partial labeled data. We also propose Avg Pegasos and Max Pegasos, which are extensions of Pegasos algorithm. We also provide mistake bounds for Avg Perceptron and regret bound for Avg Pegasos. We show the effectiveness of the proposed approaches by experimenting on various datasets and comparing them with the standard Perceptron and Pegasos.