Rethinking normalization methods in federated learning-Reference-Cited by-同舟云学术

Rethinking normalization methods in federated learning

Published:2022-12-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Workshop on Distributed Machine Learning
language:
Short-container-title:

Author:

Du Zhixu¹,Sun Jingwei¹,Li Ang¹,Chen Pin-Yu²,Zhang Jianyi¹,Li Hai "Helen"¹,Chen Yiran¹

Affiliation:

1. Duke University

2. IBM Research AI

Funder

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3565010.3569062

Reference18 articles.

1. Sanjeev Arora , Zhiyuan Li , and Kaifeng Lyu . 2019 . Theoretical Analysis of Auto Rate-Tuning by Batch Normalization . In International Conference on Learning Representations. Sanjeev Arora, Zhiyuan Li, and Kaifeng Lyu. 2019. Theoretical Analysis of Auto Rate-Tuning by Batch Normalization. In International Conference on Learning Representations.

2. Jimmy Lei Ba , Jamie Ryan Kiros, and Geoffrey E Hinton . 2016 . Layer normalization. arXiv preprint arXiv:1607.06450 (2016). Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016).

3. Enmao Diao Jie Ding and Vahid Tarokh. 2020. HeteroFL: Computation and communication efficient federated learning for heterogeneous clients. arXiv preprint arXiv:2010.01264 (2020). Enmao Diao Jie Ding and Vahid Tarokh. 2020. HeteroFL: Computation and communication efficient federated learning for heterogeneous clients. arXiv preprint arXiv:2010.01264 (2020).

4. Representative Batch Normalization with Feature Calibration

5. Kevin Hsieh , Amar Phanishayee , Onur Mutlu , and Phillip Gibbons . 2020 . The non-iid data quagmire of decentralized machine learning . In International Conference on Machine Learning. PMLR, 4387--4398 . Kevin Hsieh, Amar Phanishayee, Onur Mutlu, and Phillip Gibbons. 2020. The non-iid data quagmire of decentralized machine learning. In International Conference on Machine Learning. PMLR, 4387--4398.

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