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Vertical federated learning (VFL) allows an active party with labeled feature to leverage auxiliary features from the passive parties to improve model performance.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Mnist handwritten digit database
Yann LeCun, Corinna Cortes, and CJ Burges · 2010
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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The cifar-10 dataset
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton · 2014
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
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Communication quantization for data-parallel training of deep neural networks
Nikoli Dryden, Tim Moon, Sam Ade Jacobs, and Brian Van Essen · 2016
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Secure linear regression on vertically partitioned datasets
Adrià Gascón, Phillipp Schoppmann, Borja Balle, Mariana Raykova, Jack Doerner, Samee Zahur, and David Evans · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Sparse communication for distributed gradient descent
Alham Fikri Aji and Kenneth Heafield · 2017
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Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, and Brian Thorne · 2017
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Deep gradient compression: Reducing the communication bandwidth for distributed training
Yujun Lin, Song Han, Huizi Mao, Yu Wang, and Bill Dally · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
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Rethinking deep neural network ownership verification: Embedding passports to defeat ambiguity attacks
Lixin Fan, Kam Woh Ng, and Chee Seng Chan · 2019
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Model inversion attacks against collaborative inference
Zecheng He, Tianwei Zhang, and Ruby B Lee · 2019
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Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong · 2019
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Deep leakage from gradients
Ligeng Zhu, Zhijian Liu, , and Song Han · 2019
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Rethinking privacy preserving deep learning: How to evaluate and thwart privacy attacks
Lixin Fan, Kam Woh Ng, Ce Ju, Tianyu Zhang, Chang Liu, Chee Seng Chan, and Qiang Yang · 2020
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Instahide: Instance-hiding schemes for private distributed learning
Yangsibo Huang, Zhao Song, Kai Li, and Sanjeev Arora · 2020
Label inference attacks against vertical federated learning
Chong Fu, Xuhong Zhang, Shouling Ji, Jinyin Chen, Jingzheng Wu, Shanqing Guo, Jun Zhou, Alex X Liu, and Ting Wang · 2022
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Blindfl: Vertical federated machine learning without peeking into your data
Fangcheng Fu, Huanran Xue, Yong Cheng, Yangyu Tao, and Bin Cui · 2022
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A hybrid self-supervised learning framework for vertical federated learning
Yuanqin He, Yan Kang, Jiahuan Luo, Lixin Fan, and Qiang Yang · 2022
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Is vertical logistic regression privacy-preserving? a comprehensive privacy analysis and beyond
Yuzheng Hu, Tianle Cai, Jinyong Shan, Shange Tang, Chaochao Cai, Ethan Song, Bo Li, and Dawn Song · 2022
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Privacy-preserving federated adversarial domain adaptation over feature groups for interpretability
Y. Kang, Y. He, J. Luo, T. Fan, Y. Liu, and Q. Yang · 2022
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A review of applications in federated learning
Li Li, Yuxi Fan, Mike Tse, and Kuo-Yi Lin · 2020
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A secure federated transfer learning framework
Yang Liu, Yan Kang, Chaoping Xing, Tianjian Chen, and Qiang Yang · 2020
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Secureboost: A lossless federated learning framework
K. Cheng, T. Fan, Y. Jin, Y. Liu, T. Chen, D. Papadopoulos, and Q. Yang · 2021
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Deepip: Deep neural network intellectual property protection with passports
Lixin Fan, Kam Woh Ng, Chee Seng Chan, and Qiang Yang · 2021
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Cafe: Catastrophic data leakage in vertical federated learning
Xiao Jin, Pin-Yu Chen, Chia-Yi Hsu, Chia-Mu Yu, and Tianyi Chen · 2021
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Defending label inference and backdoor attacks in vertical federated learning
Yang Liu, Zhihao Yi, Yan Kang, Yuanqin He, Wenhan Liu, Tianyuan Zou, and Qiang Yang · 2021
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FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training
Yan Kang, Yang Liu, and Xinle Liang · 2022
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A framework for evaluating privacy-utility trade-off in vertical federated learning
Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, and Qiang Yang · 2022
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Fedipr: Ownership verification for federated deep neural network models
Bowen Li, Lixin Fan, Hanlin Gu, Jie Li, and Qiang Yang · 2022
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Label leakage and protection in two-party split learning
Oscar Li, Jiankai Sun, Xin Yang, Weihao Gao, Hongyi Zhang, Junyuan Xie, Virginia Smith, and Chong Wang · 2022
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Yang Liu, Yan Kang, Tianyuan Zou, Yanhong Pu, Yuanqin He, Xiaozhou Ye, Ye Ouyang, Ya-Qin Zhang, and Qiang Yang · 2022
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Cross-silo federated neural architecture search for heterogeneous and cooperative systems
Yang Liu, Xinle Liang, Jiahuan Luo, Yuanqin He, Tianjian Chen, Quanming Yao, and Qiang Yang · 2022
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Trading off privacy, utility and efficiency in federated learning
Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, and Qiang Yang · 2022
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Defending batch-level label inference and replacement attacks in vertical federated learning
Tianyuan Zou, Yang Liu, Yan Kang, Wenhan Liu, Yuanqin He, Zhihao Yi, Qiang Yang, and Ya-Qin Zhang · 2022
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