| Benign, tempered, or catastrophic: A taxonomy of overfitting N Mallinar, JB Simon, A Abedsoltan, P Pandit, M Belkin, P Nakkiran 36th Conference on Neural Information Processing Systems (NeurIPS 2022), 2022 | 69* | 2022 |
| Toward Large Kernel Models A Abedsoltan, M Belkin, P Pandit 40th International Conference on Machine Learning (ICML2023), 2023 | 18 | 2023 |
| Future of process safety: Insights, approaches, and potential developments H Abedsoltan, A Abedsoltan Process Safety and Environmental Protection, 2024 | 7 | 2024 |
| On emergence of clean-priority learning in early stopped neural networks C Liu, A Abedsoltan, M Belkin arXiv preprint arXiv:2306.02533, 2023 | 2 | 2023 |
| On the Nyström Approximation for Preconditioning in Kernel Machines A Abedsoltan, P Pandit, L Rademacher, M Belkin International Conference on Artificial Intelligence and Statistics, 3718-3726, 2024 | 1 | 2024 |
| Fast training of large kernel models with delayed projections A Abedsoltan, S Ma, P Pandit, M Belkin arXiv preprint arXiv:2411.16658, 2024 | | 2024 |
| Context-Scaling versus Task-Scaling in In-Context Learning A Abedsoltan, A Radhakrishnan, J Wu, M Belkin arXiv preprint arXiv:2410.12783, 2024 | | 2024 |
| Uncertainty Estimation with Recursive Feature Machines D Gedon, A Abedsoltan, TB Schön, M Belkin The 40th Conference on Uncertainty in Artificial Intelligence, 2024 | | 2024 |
| On Feature Learning of Recursive Feature Machines and Automatic Relevance Determination D Gedon, A Abedsoltan, TB Schön, M Belkin UniReps: the First Workshop on Unifying Representations in Neural Models, 0 | | |
Mikhail (Misha) BelkinProfessor of Data Science, Halıcıoğlu Data Science Institute, CSE, UCSD, Amazon ScholarVerified email at ucsd.edu
