A4 Article in conference proceedings
OnMLM : An Online Formulation for the Minimal Learning Machine (2019)
Matias, A. L. S., Mattos, C. L. C., Kärkkäinen, T., Gomes, J. P.P., & Rocha Neto, A. R. D. (2019). OnMLM : An Online Formulation for the Minimal Learning Machine. In I. Rojas, G. Joya, & A. Catala (Eds.), IWANN 2019 : Advances in Computational Intelligence : 15th International Work-Conference on Artificial Neural Networks, Proceedings, Part I (pp. 557-568). Springer. Lecture Notes in Computer Science, 11506. https://doi.org/10.1007/978-3-030-20521-8_46
JYU authors or editors
Publication details
All authors or editors: Matias, Alan L. S.; Mattos, César L. C.; Kärkkäinen, Tommi; Gomes, João P. P.; Rocha Neto, Ajalmar R. da
Parent publication: IWANN 2019 : Advances in Computational Intelligence : 15th International Work-Conference on Artificial Neural Networks, Proceedings, Part I
Parent publication editors: Rojas, Ignacio; Joya, Gonzalo; Catala, Andreu
Place and date of conference: Gran Canaria, Spain, 12.-14.6.2019
ISBN: 978-3-030-20520-1
eISBN: 978-3-030-20521-8
Journal or series: Lecture Notes in Computer Science
ISSN: 0302-9743
eISSN: 1611-3349
Publication year: 2019
Number in series: 11506
Pages range: 557-568
Number of pages in the book: 940
Publisher: Springer
Place of Publication: Cham
Publication country: Switzerland
Publication language: English
DOI: https://doi.org/10.1007/978-3-030-20521-8_46
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/65933
Abstract
Minimal Learning Machine (MLM) is a nonlinear learning algorithm designed to work on both classification and regression tasks. In its original formulation, MLM builds a linear mapping between distance matrices in the input and output spaces using the Ordinary Least Squares (OLS) algorithm. Although the OLS algorithm is a very efficient choice, when it comes to applications in big data and streams of data, online learning is more scalable and thus applicable. In that regard, our objective of this work is to propose an online version of the MLM. The Online Minimal Learning Machine (OnMLM), a new MLM-based formulation capable of online and incremental learning. The achievements of OnMLM in our experiments, in both classification and regression scenarios, indicate its feasibility for applications that require an online learning framework.
Keywords: machine learning; stochastic processes; big data
Free keywords: online learning; incremental learning; stochastic optimization; Minimal Learning Machine
Contributing organizations
Related projects
- Competitive funding to strengthen universities’ research profiles. Profiling actions at the JYU, round 3
- Hämäläinen, Keijo
- Research Council of Finland
- STRUCTURE PREDICTION OF HYBRID NANOPARTICLES VIA ARTIFICIAL INTELLIGENCE
- Kärkkäinen, Tommi
- Research Council of Finland
Ministry reporting: Yes
Reporting Year: 2019
JUFO rating: 1