| Estimation of energy consumption in machine learning E García-Martín, CF Rodrigues, G Riley, H Grahn Journal of Parallel and Distributed Computing 134, 75-88, 2019 | 571 | 2019 |
| Hashtags and followers: An experimental study of the online social network Twitter EG Martín, N Lavesson, M Doroud Social Network Analysis and Mining 6 (1), 12, 2016 | 35 | 2016 |
| How to measure energy consumption in machine learning algorithms E García-Martín, N Lavesson, H Grahn, E Casalicchio, V Boeva ECML PKDD 2018 Workshops: Nemesis 2018, UrbReas 2018, SoGood 2018, IWAISe …, 2019 | 33 | 2019 |
| Identification of Energy Hotspots: A Case Study of the Very Fast Decision Tree E Garcia-Martin, N Lavesson, H Grahn Green, Pervasive, and Cloud Computing: 12th International Conference, GPC …, 2017 | 29 | 2017 |
| Energy Efficiency in Machine Learning: A position paper E García-Martín, N Lavesson, H Grahn, V Boeva 30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS …, 2017 | 18 | 2017 |
| Hoeffding trees with nmin adaptation E García-Martín, N Lavesson, H Grahn, E Casalicchio, V Boeva 2018 IEEE 5th International Conference on Data Science and Advanced …, 2018 | 14 | 2018 |
| Energy-aware very fast decision tree E García-Martín, N Lavesson, H Grahn, E Casalicchio, V Boeva International Journal of Data Science and Analytics 11, 105-126, 2021 | 11 | 2021 |
| Energy efficiency analysis of the very fast decision tree algorithm E Garcia-Martin, N Lavesson, H Grahn Trends in Social Network Analysis: Information Propagation, User Behavior …, 2017 | 10 | 2017 |
| Energy modeling of Hoeffding tree ensembles E García-Martín, A Bifet, N Lavesson Intelligent Data Analysis 25 (1), 81-104, 2021 | 9 | 2021 |
| Energy Efficiency in Data Stream Mining E Garcia-Martin, N Lavesson, H Grahn Proceedings of the 2015 IEEE/ACM International Conference on Advances in …, 2015 | 9 | 2015 |
| Green accelerated Hoeffding tree E Garcia-Martin, A Bifet, N Lavesson, R König, H Linusson arXiv preprint arXiv:2205.03184, 2022 | 8 | 2022 |
| Extraction and energy efficient processing of streaming data E García-Martín Blekinge Tekniska Högskola, 2017 | 5 | 2017 |
| Energy Efficiency in Machine Learning: Approaches to Sustainable Data Stream Mining E García Martín Blekinge Tekniska Högskola, 2020 | 4 | 2020 |
| Is it ethical to avoid error analysis? E García-Martín, N Lavesson 2017 Workshop on Fairness, Accountability, and Transparency in Machine …, 2017 | 4 | 2017 |
| Trend analysis to automatically identify heat program changes S Abghari, E Garcia-Martin, C Johansson, N Lavesson, H Grahn Energy Procedia 116, 407-415, 2017 | 4 | 2017 |
| Handling non-linear relations in support vector machines through hyperplane folding L Lundberg, H Lennerstad, V Boeva, E García-Martín Proceedings of the 2019 11th International Conference on Machine Learning …, 2019 | 3 | 2019 |
| Is it Ethical to Avoid Error Analysis? EG Martín, N Lavesson arXiv, 2017 | | 2017 |
| Hyperplane Folding–a Way to Increase the Margin in Support Vector Machines L Lundberg, H Lennerstad, E Garcia-Martin, N Lavesson, V Boeva | | |
Håkan GrahnProfessor of Computer Engineering, Blekinge Institute of Technology, SwedenVerified email at bth.se
