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Margalit R Glasgow
Margalit R Glasgow
在 stanford.edu 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
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
1672020
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
412022
Approximate gradient coding with optimal decoding
M Glasgow, M Wootters
IEEE Journal on Selected Areas in Information Theory 2 (3), 855-866, 2021
222021
Asynchronous distributed optimization with stochastic delays
MR Glasgow, M Wootters
International Conference on Artificial Intelligence and Statistics, 9247-9279, 2022
112022
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, ...
arXiv preprint arXiv:2405.11667, 2024
8*2024
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
82024
The exact rank of sparse random graphs
M Glasgow, M Kwan, A Sah, M Sawhney
arXiv preprint arXiv:2303.05435, 2023
72023
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
52023
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
32024
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
32024
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
32022
On the rank, kernel, and core of sparse random graphs
P DeMichele, M Glasgow, A Moreira
Random Structures & Algorithms, 2021
3*2021
Tight Bounds for -Regret via the Decision-Estimation Coefficient
M Glasgow, A Rakhlin
arXiv preprint arXiv:2303.03327, 2023
2023
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