Nery Riquelme-Granada, together with his supervisors Dr. Khuong An Nguyen and Prof. Zhiyuan Luo, has received the Best Student Paper Award, at the 9th International Conference on Data Science, Technology and Applications (DATA 2020).
Nery is our Teaching Fellow, and 4th year Ph.D student, working on Machine Learning approaches for Coresets constructions.
DATA is one of the premier international conferences in databases, big data, data mining, data management, data security and other aspects of information systems. The 2020 conference was based in France from 7-9 July (http://www.dataconference.org).
Title - "On generating efficient data summaries for logistic regression: A coreset-based approach"
Award - Best Student Paper
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 empirical performance of coresets.
Authors - Nery Riquelme-Granada, Dr. Khuong An Nguyen, and Prof. Zhiyuan Luo.
Conference - The 9th International Conference on Data Science, Technology and Applications (DATA 2020 - http://www.dataconference.org)