Anton Lee

Anton Lee profile picture

PhD Student
School of Engineering and Computer Science

Thesis Info

Research Interests: Continual Learning Deep Learning
Thesis Title: Continual Learning
Supervisor: Dr Heitor Murilo Gomes, Prof Bastiaan Kleijn, Dr Yaqian Zhang

 

Doherty, W., Lee, A., & Gomes, H. M. (2025). CLOFAI: A dataset of real and fake image classification tasks for continual learning. CoRR, abs/2501.11140. https://doi.org/10.48550/ARXIV.2501.11140
Gomes, H. M., Lee, A., Gunasekara, N., Sun, Y., Cassales, G. W., Liu, J., Heyden, M., Cerqueira, V., Bahri, M., Koh, Y. S., Pfahringer, B., & Bifet, A. (2025). CapyMOA: Efficient machine learning for data streams in python. CoRR, abs/2502.07432. https://doi.org/10.48550/ARXIV.2502.07432
Lee, A., Gomes, H. M., & Zhang, Y. (2022). Balancing the stability-plasticity dilemma with online stability tuning for continual learning. International Joint Conference on Neural Networks, IJCNN 2022, Padua, Italy, July 18-23, 2022, 1–8. https://doi.org/10.1109/IJCNN55064.2022.9892055
Lee, A., Gomes, H. M., Zhang, Y., & Kleijn, W. B. (2025). Kolmogorov-arnold networks still catastrophically forget but differently from MLP. In T. Walsh, J. Shah, & Z. Kolter (Eds.), AAAI-25, sponsored by the association for the advancement of artificial intelligence, february 25—March 4, 2025, philadelphia, PA, USA (pp. 18053–18061). AAAI Press. https://doi.org/10.1609/AAAI.V39I17.33986
Lee, A., Zhang, Y., Gomes, H. M., Bifet, A., & Pfahringer, B. (2023). Look at me, no replay! SurpriseNet: Anomaly detection inspired class incremental learning. In I. Frommholz, F. Hopfgartner, M. Lee, M. Oakes, M. Lalmas, M. Zhang, & R. L. T. Santos (Eds.), Proceedings of the 32nd ACM international conference on information and knowledge management, CIKM 2023, birmingham, united kingdom, october 21-25, 2023 (pp. 4038–4042). ACM. https://doi.org/10.1145/3583780.3615236