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Authors: Nery Riquelme-Granada ; Khuong An Nguyen and Zhiyuan Luo

Affiliation: Department of Computer Science, Royal Holloway University of London, Egham, Surrey, TW20 0EX, U.K.

Keyword(s): Coresets, Data Summaries, Logistic Regression, Large-data, Computing Time.

Abstract: In the era of datasets of unprecedented sizes, data compression techniques are an attractive approach for speeding up machine learning algorithms. One of the most successful paradigms for achieving good-quality compression is that of coresets: small summaries of data that act as proxies to the original input data. Even though coresets proved to be extremely useful to accelerate unsupervised learning problems, applying them to supervised learning problems may bring unexpected computational bottlenecks. We show that this is the case for Logistic Regression classification, and hence propose two methods for accelerating the computation of coresets for this problem. When coresets are computed using our methods on three public datasets, computing the coreset and learning from it is, in the worst case, 11 times faster than learning directly from the full input data, and 34 times faster in the best case. Furthermore, our results indicate that our accelerating approaches do not degrade the em pirical performance of coresets. (More)

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Paper citation in several formats:
Riquelme-Granada, N.; Nguyen, K. and Luo, Z. (2020). On Generating Efficient Data Summaries for Logistic Regression: A Coreset-based Approach. In Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-440-4; ISSN 2184-285X, SciTePress, pages 78-89. DOI: 10.5220/0009823200780089

@conference{data20,
author={Nery Riquelme{-}Granada. and Khuong An Nguyen. and Zhiyuan Luo.},
title={On Generating Efficient Data Summaries for Logistic Regression: A Coreset-based Approach},
booktitle={Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA},
year={2020},
pages={78-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009823200780089},
isbn={978-989-758-440-4},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Data Science, Technology and Applications - DATA
TI - On Generating Efficient Data Summaries for Logistic Regression: A Coreset-based Approach
SN - 978-989-758-440-4
IS - 2184-285X
AU - Riquelme-Granada, N.
AU - Nguyen, K.
AU - Luo, Z.
PY - 2020
SP - 78
EP - 89
DO - 10.5220/0009823200780089
PB - SciTePress