| Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE G Douzas, F Bacao, F Last Information sciences 465, 1-20, 2018 | 1106 | 2018 |
| Oversampling for imbalanced learning based on k-means and smote. arXiv 2017 F Last, G Douzas, F Bacao arXiv preprint arXiv:1711.00837 2, 1711 | 19 | 1711 |
| Human-machine collaboration for medical image segmentation M Ravanbakhsh, V Tschernezki, F Last, T Klein, K Batmanghelich, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 15 | 2020 |
| Predicting Memory Compiler Performance Outputs Using Feed-forward Neural Networks F Last, M Haeberlein, U Schlichtmann ACM Transactions on Design Automation of Electronic Systems (TODAES) 25 (5 …, 2020 | 8 | 2020 |
| Feeding Hungry Models Less: Deep Transfer Learning for Embedded Memory PPA Models F Last, U Schlichtmann 2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD), 1-6, 2021 | 6 | 2021 |
| Partial sharing neural networks for multi-target regression on power and performance of embedded memories F Last, U Schlichtmann Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD, 123-128, 2020 | 5 | 2020 |
| Predicting Failure Distributions of SRAM Arrays by Using Extreme Value Statistic, Bit Cell Simulation, and Machine Learning T Pompl, TK Bashir, M Voelker, F Last, M Ostermayr IEEE Transactions on Device and Materials Reliability 23 (3), 363-369, 2023 | 1 | 2023 |
| Differentially Evolving Memory Ensembles: Pareto Optimization based on Computational Intelligence for Embedded Memories on a System Level F Last, C Yeni, U Schlichtmann 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), 506-512, 2022 | 1 | 2022 |
| Human-Machine Collaboration for Medical Image Segmentation F Last, T Klein, M Ravanbakhsh, M Nabi, K Batmanghelich, V Tresp | 1 | 2018 |
| Training PPA Models for Embedded Memories on a Low-data Diet F Last, U Schlichtmann ACM Transactions on Design Automation of Electronic Systems 28 (2), 1-24, 2022 | | 2022 |
Fernando BacaoNOVA IMS, Universidade Nova de Lisboa在 novaims.unl.pt 的电子邮件经过验证
