PSLF: Defending Against Label Leakage in Split Learning-Reference-Cited by-同舟云学术

PSLF: Defending Against Label Leakage in Split Learning

Published:2023-10-21 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
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Author:

Wan Xinwei¹^ORCID,Sun Jiankai²^ORCID,Wang Shengjie²^ORCID,Chen Lei³^ORCID,Zheng Zhenzhe¹^ORCID,Wu Fan¹^ORCID,Chen Guihai¹^ORCID

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Bytedance Inc., Seattle, USA

3. Bytedance Inc., San Jose, USA

Funder

China NSF grant

Shanghai Science and Technology fund

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3583780.3615019

Reference40 articles.

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3. Avazu. 2015. Avazu click-through rate prediction. https://www.kaggle.com/c/ avazu-ctr-prediction/data. Avazu. 2015. Avazu click-through rate prediction. https://www.kaggle.com/c/ avazu-ctr-prediction/data.

4. Efficient and Private ECG Classification on the Edge Using a Modified Split Learning Mechanism

5. Yuanqin Cai and Tongquan Wei . 2022 . Efficient Split Learning with Non-iid Data. In 23rd IEEE International Conference on Mobile Data Management. 128--136 . Yuanqin Cai and Tongquan Wei. 2022. Efficient Split Learning with Non-iid Data. In 23rd IEEE International Conference on Mobile Data Management. 128--136.