The following publications are possibly variants of this publication:
- ACCEL: an efficient and privacy-preserving federated logistic regression scheme over vertically partitioned dataJiaqi Zhao 0005, Hui Zhu 0001, Fengwei Wang, Rongxing Lu, Hui Li 0006, Zhongmin Zhou, Haitao Wan. chinaf, 65(7):1-2, 2022. [doi]
- Efficient and Privacy-Preserving Logistic Regression Scheme based on Leveled Fully Homomorphic EncryptionChengjin Liu, Zoe Lin Jiang, Xin Zhao, Qian Chen 0028, Junbin Fang, Daojing He, Jun Zhang, Xuan Wang. infocom 2022: 1-6 [doi]
- Privacy-Preserving Multi-User Joint Data Logistic Regression Inference SchemeYubao Zhang, Lin Tang, Lixuan Che, Chaozhang Liu, Entang Li, Hongwei Xing, Jianhui Zhang, Guandong Di. nana 2023: 193-201 [doi]
- A privacy-preserving logistic regression-based diagnosis scheme for digital healthcareYousheng Zhou, Liyuan Song, Yuanni Liu, Pandi Vijayakumar, Brij B. Gupta, Wadee Alhalabi, Hind Alsharif. fgcs, 144:63-73, July 2023. [doi]
- PEVLR: A New Privacy-Preserving and Efficient Approach for Vertical Logistic RegressionSihan Mao, Xiaolin Zheng, Jianguang Zhang, Xiaodong Hu. iconip 2024: 380-392 [doi]
- VFLR: An Efficient and Privacy-Preserving Vertical Federated Framework for Logistic RegressionJiaqi Zhao 0005, Hui Zhu 0001, Fengwei Wang, Rongxing Lu, Ermei Wang, Linfeng Li, Hui Li 0006. tcc, 11(4):3326-3340, October - December 2023. [doi]
- Efficient and Privacy-Preserving Logistic Regression Prediction over Vertically Partitioned DataJiaqi Zhao 0005, Hui Zhu 0001, Fengwei Wang, Rongxing Lu, Hui Li 0006. globecom 2023: 4253-4258 [doi]
- Privacy preserving based logistic regression on big dataYongkai Fan, Jianrong Bai, Xia Lei, Yuqing Zhang, Bin Zhang 0008, Kuan-Ching Li, Gang Tan. jnca, 171:102769, 2020. [doi]