引用次数
引用: 756
H-指数: 4
I10-指数 : 3
出版物: 6
Multi-Task Learning with Deep Neural Networks: A Survey.
Michael Crawshaw
arXiv: Learning
291
2020
Fast composite optimization and statistical recovery in federated learning
Yajie Bao , Michael Crawshaw , Shan Luo , Mingrui Liu
Smpte Journal 1508 -1536
2
2022
Robustness to unbounded smoothness of generalized signsgd
Michael Crawshaw , Mingrui Liu , Francesco Orabona , Wei Zhang
Advances in neural information processing systems 35 9955 -9968
36
2022
Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
Michael Crawshaw , Yajie Bao , Mingrui Liu
Advances in Neural Information Processing Systems 36
4
2024
EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
Michael Crawshaw , Yajie Bao , Mingrui Liu
International Conference on Learning Representations
4
2023
Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective
Yajie Bao , Michael Crawshaw , Mingrui Liu
Forty-first International Conference on Machine Learning