The eigenlearning framework: A conservation law perspective on kernel regression and wide neural networks JB Simon, M Dickens, D Karkada, MR DeWeese arXiv preprint arXiv:2110.03922, 2021 | 15 | 2021 |
The eigenlearning framework: A conservation law perspective on kernel ridge regression and wide neural networks JB Simon, M Dickens, D Karkada, M Deweese Transactions on Machine Learning Research, 2023 | 7 | 2023 |
More is better in modern machine learning: when infinite overparameterization is optimal and overfitting is obligatory JB Simon, D Karkada, N Ghosh, M Belkin arXiv preprint arXiv:2311.14646, 2023 | 6 | 2023 |
The lazy (NTK) and rich (P) regimes: a gentle tutorial D Karkada arXiv preprint arXiv:2404.19719, 2024 | | 2024 |
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory JB Simon, D Karkada, N Ghosh, M Belkin The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
Using Deep Neural Networks to Identify Natural and Anthropogenic Disturbances in Seagrass Meadows Observed in Side-scan Sonar Images D Karkada, MS Ballard, K Lee, AF Rahman, P Wilson Ocean Sciences Meeting 2020, 2020 | | 2020 |