| 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 | 235 | 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 | 82 | 2022 |
| 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 | 39 | 2023 |
| The limits and potentials of local sgd for distributed heterogeneous learning with intermittent communication KK Patel, M Glasgow, A Zindari, L Wang, SU Stich, Z Cheng, N Joshi, ... The Thirty Seventh Annual Conference on Learning Theory, 4115-4157, 2024 | 30* | 2024 |
| Approximate gradient coding with optimal decoding M Glasgow, M Wootters IEEE journal on selected areas in information theory 2 (3), 855-866, 2021 | 30 | 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, 57367-57480, 2023 | 23 | 2023 |
| Asynchronous distributed optimization with stochastic delays MR Glasgow, M Wootters International Conference on Artificial Intelligence and Statistics, 9247-9279, 2022 | 20 | 2022 |
| The exact rank of sparse random graphs M Glasgow, M Kwan, A Sah, M Sawhney arXiv preprint arXiv:2303.05435, 2023 | 15 | 2023 |
| A central limit theorem for the matching number of a sparse random graph M Glasgow, M Kwan, A Sah, M Sawhney Journal of the London Mathematical Society 111 (4), e70101, 2025 | 14 | 2025 |
| 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 | 8 | 2022 |
| On the rank, kernel, and core of sparse random graphs P DeMichele, M Glasgow, A Moreira Random Structures & Algorithms, 2024 | 7* | 2024 |
| Feature dropout: Revisiting the role of augmentations in contrastive learning A Tamkin, M Glasgow, X He, N Goodman arXiv preprint arXiv:2212.08378, 2022 | 7 | 2022 |
| Tight Bounds for -Regret via the Decision-Estimation Coefficient M Glasgow, A Rakhlin arXiv preprint arXiv:2303.03327, 2023 | 5 | 2023 |
| 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, 61806-61835, 2023 | 3 | 2023 |
| Propagation of Chaos in One-hidden-layer Neural Networks beyond Logarithmic Time M Glasgow, D Wu, J Bruna arXiv preprint arXiv:2504.13110, 2025 | 2* | 2025 |
| Convergence of Distributed Adaptive Optimization with Local Updates Z Cheng, M Glasgow arXiv preprint arXiv:2409.13155, 2024 | 2 | 2024 |
| Feature Learning in Neural Networks and Other Stochastic Explorations M Glasgow Stanford University, 2024 | | 2024 |
