| A comparative node evaluation model for highly heterogeneous massive‐scale Internet of Things‐Mist networks A Shahraki, M Geitle, Ø Haugen Transactions on Emerging Telecommunications Technologies, 2020 | 17 | 2020 |
| A new baseline for automated hyper-parameter optimization M Geitle, R Olsson Machine Learning, Optimization, and Data Science: 5th International …, 2019 | 11 | 2019 |
| Exploring the Hyperparameters of XGBoost Through 3D Visualizations. OE Ørebæk, M Geitle AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021 | 10 | 2021 |
| Improving differential evolution using inductive programming M Geitle | 6 | 2017 |
| A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost A Shahraki, M Geitle, Ø Haugen 2019 4th International Conference on Smart and Sustainable Technologies …, 2019 | 5 | 2019 |
| Using automatic programming to design improved variants of differential evolution M Geitle, R Olsson 2017 21st Asia Pacific Symposium on Intelligent and Evolutionary Systems …, 2017 | 3 | 2017 |
| Deep Ensemble Transformers for Dimensionality Reduction M Nareklishvili, M Geitle IEEE Transactions on Neural Networks and Learning Systems, 2024 | 1 | 2024 |
| Evaluating Population Based Training on Small Datasets F Tennebø, M Geitle 2019: Norsk Informatikkonferanse, 2019 | 1 | 2019 |
| Improving competitive differential evolution using automatic programming M Geitle, R Olsson 2017 4th International Conference on Systems and Informatics (ICSAI), 2018 | | 2018 |
Amin ShahrakiPhD, SMIEEE, Research Scientist in Industrial IoTAdresse e-mail validée de ieee.org