Glasgow, Margalit

9 publications

ICLR 2025 Convergence of Distributed Adaptive Optimization with Local Updates Ziheng Cheng, Margalit Glasgow
COLT 2025 Mean-Field Analysis of Polynomial-Width Two-Layer Neural Network Beyond Finite Time Horizon Margalit Glasgow, Denny Wu, Joan Bruna
NeurIPSW 2024 Convergence of Distributed Adaptive Optimization with Local Updates Ziheng Cheng, Margalit Glasgow
ICLR 2024 SGD Finds Then Tunes Features in Two-Layer Neural Networks with Near-Optimal Sample Complexity: A Case Study in the XOR Problem Margalit Glasgow
COLT 2024 The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication Kumar Kshitij Patel, Margalit Glasgow, Ali Zindari, Lingxiao Wang, Sebastian U Stich, Ziheng Cheng, Nirmit Joshi, Nathan Srebro
NeurIPS 2023 Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time Arvind Mahankali, Haochen Zhang, Kefan Dong, Margalit Glasgow, Tengyu Ma
NeurIPS 2023 Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning Alex Tamkin, Margalit Glasgow, Xiluo He, Noah Goodman
ICLR 2023 Max-Margin Works While Large Margin Fails: Generalization Without Uniform Convergence Margalit Glasgow, Colin Wei, Mary Wootters, Tengyu Ma
ICMLW 2023 On the Still Unreasonable Effectiveness of Federated Averaging for Heterogeneous Distributed Learning Kumar Kshitij Patel, Margalit Glasgow, Lingxiao Wang, Nirmit Joshi, Nathan Srebro