| Determination of RNA structural diversity and its role in HIV-1 RNA splicing PJ Tomezsko, VDA Corbin, P Gupta, H Swaminathan, M Glasgow, ... Nature 582 (7812), 438-442, 2020 | 156 | 2020 |
| Sharp bounds for federated averaging (local sgd) and continuous perspective MR Glasgow, H Yuan, T Ma International Conference on Artificial Intelligence and Statistics, 9050-9090, 2022 | 36 | 2022 |
| Approximate gradient coding with optimal decoding M Glasgow, M Wootters IEEE Journal on Selected Areas in Information Theory 2 (3), 855-866, 2021 | 20 | 2021 |
| Beyond ntk with vanilla gradient descent: A mean-field analysis of neural networks with polynomial width, samples, and time A Mahankali, H Zhang, K Dong, M Glasgow, T Ma Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| The exact rank of sparse random graphs M Glasgow, M Kwan, A Sah, M Sawhney arXiv preprint arXiv:2303.05435, 2023 | 7 | 2023 |
| Asynchronous distributed optimization with stochastic delays MR Glasgow, M Wootters International Conference on Artificial Intelligence and Statistics, 9247-9279, 2022 | 7 | 2022 |
| On the still unreasonable effectiveness of federated averaging for heterogeneous distributed learning KK Patel, M Glasgow, L Wang, N Joshi, N Srebro Federated Learning and Analytics in Practice: Algorithms, Systems …, 2023 | 4 | 2023 |
| Max-margin works while large margin fails: Generalization without uniform convergence M Glasgow, C Wei, M Wootters, T Ma arXiv preprint arXiv:2206.07892, 2022 | 4 | 2022 |
| On the rank, kernel, and core of sparse random graphs P DeMichele, M Glasgow, A Moreira arXiv preprint arXiv:2105.11718, 2021 | 3* | 2021 |
| Feature dropout: Revisiting the role of augmentations in contrastive learning A Tamkin, M Glasgow, X He, N Goodman Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| A central limit theorem for the matching number of a sparse random graph M Glasgow, M Kwan, A Sah, M Sawhney arXiv preprint arXiv:2402.05851, 2024 | 2 | 2024 |
| SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem M Glasgow arXiv preprint arXiv:2309.15111, 2023 | 2 | 2023 |
| Tight Bounds for -Regret via the Decision-Estimation Coefficient M Glasgow, A Rakhlin arXiv preprint arXiv:2303.03327, 2023 | | 2023 |
