Eva Garcia Martin

PhD student in Machine Learning at Blekinge Institute of Technology, in Sweden. I am working under the project Scalable resource- efficient systems for big data analytics funded by the Knowledge Foundation (Sweden), advised by Niklas Lavesson and Håkan grahn.

The main focus of my thesis is on making machine learning algorithms more energy efficiency. In particular, I have studied the energy consumption patterns of streaming algorithms, and then proposed new algorithm extensions that reduce their energy consumption

Projekt och publikationer

Pågående projekt
Scalable resource- efficient systems for big data analytics

Nyligen publicerat
Eva García Martín, Albert Bifet, Niklas Lavesson, "Energy Modeling of Hoeffding Tree Ensembles", Intelligent Data Analysis, ISSN 1088-467X, EISSN 1571-4128, Vol. 25, nr 1, pp. 81 - 104, IOS Press, 2021
Eva García Martín, Niklas Lavesson, Håkan Grahn, Emiliano Casalicchio, Veselka Boeva, "Energy-Aware Very Fast Decision Tree", International Journal of Data Science and Analytics, ISSN 2364-415X, Vol. 11, nr 2, pp. 105 - 126, Springer Science+Business Media B.V., 2021
Eva García Martín, "Energy Efficiency in Machine Learning", Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090, EISSN 12153, EISSN 2, Blekinge Tekniska Högskola, 2020
Eva García Martín, Crefeda Faviola Rodrigues, Graham Riley, Håkan Grahn, "Estimation of energy consumption in machine learning", Journal of Parallel and Distributed Computing, ISSN 0743-7315, EISSN 1096-0848, Vol. 134, pp. 75 - 88, Academic Press, 2019
Lars Lundberg, Håkan Lennerstad, Veselka Boeva, Eva García Martín, "Handling non-linear relations in support vector machines through hyperplane folding", ACM International Conference Proceeding Series, Association for Computing Machinery, 2019