| Reinforcement learning for personalization: a systematic literature review F den Hengst, EM Grua, A el Hassouni, M Hoogendoorn | 25 | 2020 |
| Self-Adaptation in Mobile Apps: a Systematic Literature Study EM Grua, I Malavolta, P Lago SEAMS 2019, 2019 | 21 | 2019 |
| A framework for the automatic execution of measurement-based experiments on Android devices I Malavolta, EM Grua, CY Lam, R De Vries, F Tan, E Zielinski, M Peters, ... Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 18 | 2020 |
| Investigating the correlation between performance scores and energy consumption of mobile web apps K Chan-Jong-Chu, T Islam, MM Exposito, S Sheombar, C Valladares, ... | 12 | 2020 |
| Exploring Clustering Techniques for Effective Reinforcement Learning based Personalization for Health and Wellbeing EM Grua, M Hoogendoorn 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 813-820, 2018 | 12 | 2018 |
| Towards a sustainable business model for smartphones: Combining product-service systems with modularity. AF Schneider, S Matinfar, EM Grua, D Casado-Mansilla, L Cordewener ICT4S, 82-99, 2018 | 11 | 2018 |
| A Reference Architecture for Personalized and Self-adaptive e-Health Apps EM Grua, M De Sanctis, P Lago Software Architecture: 14th European Conference, {ECSA} 2020 Tracks and …, 2020 | 8 | 2020 |
| CluStream-GT: Online Clustering for Personalization in the Health Domain EM Grua, M Hoogendoorn, I Malavolta, P Lago, AE Eiben IEEE/WIC/ACM International Conference on Web Intelligence, 270-275, 2019 | 8 | 2019 |
| Social Sustainability in the e-Health Domain via Personalized and Self-Adaptive Mobile Apps EM Grua, MD Sanctis, I Malavolta, M Hoogendoorn, P Lago Software Sustainability, 301-328, 2021 | 6 | 2021 |
| An evaluation of the effectiveness of personalization and self-adaptation for e-Health apps EM Grua, M De Sanctis, I Malavolta, M Hoogendoorn, P Lago Information and Software Technology, 106841, 2022 | 4 | 2022 |
| Quantifying the Effects of Ground Truth Annotation Quality on Object Detection and Instance Segmentation Performance C Agnew, C Eising, P Denny, A Scanlan, P Van De Ven, EM Grua IEEE Access, 2023 | 1 | 2023 |
| Modelling and predicting User Engagement in mobile applications E Barbaro, EM Grua, I Malavolta, M Stercevic, E Weusthof, ... Data Science, 1-17, 2019 | 1 | 2019 |
| Detecting the Overfilled Status of Domestic and Commercial Bins using Computer Vision C Agnew, D Mewada, EM Grua, C Eising, P Denny, M Heffernan, ... Intelligent Systems with Applications, 200229, 2023 | | 2023 |
| Other PHQ-9 item pairings are better than the PHQ-2: A Machine Learning analysis D Glavin, E Maekawa, EM Grua, CA Nakamura, M Scazufca, R Araya, ... Procedia Computer Science 206, 101-110, 2022 | | 2022 |
| A Machine Learning approach to optimize the assessment of depressive symptomatology M Eduardo, G Darragh, GE Martino, NC Akemi, S Marcia, A Ricardo Procedia Computer Science 206, 111-120, 2022 | | 2022 |
| The Future of E-Health is Mobile: Combining AI and Self-Adaptation to Create Adaptive E-Health Mobile Applications EM Grua | | 2021 |
| VU Research Portal EM Grua, M Hoogendoorn, I Malavolta, P Lago, AE Eiben | | 2019 |
Mark HoogendoornFull Professor of Artificial Intelligence, VU University AmsterdamVerified email at cs.vu.nl
