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The Ethereal
Online Algorithms for Multiclass Classification using Partial Labels
December 24, 2019 ยท Declared Dead ยท ๐ Pacific-Asia Conference on Knowledge Discovery and Data Mining
"No code URL or promise found in abstract"
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Authors
Rajarshi Bhattacharjee, Naresh Manwani
arXiv ID
1912.11367
Category
cs.LG: Machine Learning
Cross-listed
stat.ML
Citations
3
Venue
Pacific-Asia Conference on Knowledge Discovery and Data Mining
Last Checked
3 months ago
Abstract
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.
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