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Vertical Federated Learning (VFL) is widely utilized in real-world applications to enable collaborative learning while protecting data privacy and safety.
The information bottleneck method
Naftali Tishby, Fernando C Pereira, and William Bialek · 1999
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Differential privacy
Cynthia Dwork · 2006
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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An intuitive proof of the data processing inequality
Normand J Beaudry and Renato Renner · 2011
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Privacy-preserving deep learning
Reza Shokri and Vitaly Shmatikov · 2015
Earlier work this paper cites.
Deep learning and the information bottleneck principle
Naftali Tishby and Noga Zaslavsky · 2015
Earlier work this paper cites.
Deep variational information bottleneck
Alexander A Alemi, Ian Fischer, Joshua V Dillon, and Kevin Murphy · 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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Federated learning of deep networks using model averaging
H. Brendan McMahan, Eider Moore, Daniel Ramage, and Blaise Agüera y Arcas · 2016
Earlier work this paper cites.
Federated learning of deep networks using model averaging
H Brendan McMahan, Eider Moore, Daniel Ramage, and Blaise Agüera y Arcas · 2016
Earlier work this paper cites.
Sparse communication for distributed gradient descent
Alham Fikri Aji and Kenneth Heafield · 2017
Earlier work this paper cites.
Deep gradient compression: Reducing the communication bandwidth for distributed training
Yujun Lin, Song Han, Huizi Mao, Yu Wang, and William J Dally · 2017
Earlier work this paper cites.
Secure federated transfer learning
Yang Liu, Tianjian Chen, and Qiang Yang · 2018
Earlier work this paper cites.
Fdml: A collaborative machine learning framework for distributed features
Yaochen Hu, Di Niu, Jianming Yang, and Shengping Zhou · 2019
Earlier work this paper cites.
A communication efficient collaborative learning framework for distributed features
Yang Liu, Yan Kang, Xin wei Zhang, Liping Li, Yong Cheng, Tianjian Chen, M. Hong, and Q. Yang · 2019
Cited alongside, same era.
A communication efficient collaborative learning framework for distributed features
Yang Liu, Yan Kang, Xinwei Zhang, Liping Li, Yong Cheng, Tianjian Chen, Mingyi Hong, and Qiang Yang · 2019
Cited alongside, same era.
Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong · 2019
Cited alongside, same era.
Federated learning
Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, and Han Yu · 2019
Cited alongside, same era.
Deep leakage from gradients
Ligeng Zhu, Zhijian Liu, and Song Han · 2019
Cited alongside, same era.
How to backdoor federated learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov · 2020
Privacy-preserving collaborative learning with automatic transformation search
Wei Gao, Shangwei Guo, Tianwei Zhang, Han Qiu, Yonggang Wen, and Yang Liu · 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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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 · 2021
Later among the works it cites.
Rvfr: Robust vertical federated learning via feature subspace recovery
Jing Liu, Chulin Xie, Krishnaram Kenthapadi, Oluwasanmi O Koyejo, and Bo Li · 2021
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Feature Inference Attack on Model Predictions in Vertical Federated Learning
Xinjian Luo, Yuncheng Wu, Xiaokui Xiao, and Beng Chin Ooi · 2021
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Cited alongside, same era.
A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses
Malik Boudiaf, Jérôme Rony, Imtiaz Masud Ziko, Eric Granger, Marco Pedersoli, Pablo Piantanida, and Ismail Ben Ayed · 2020
Cited alongside, same era.
Federated learning for privacy-preserving ai
Yong Cheng, Yang Liu, Tianjian Chen, and Qiang Yang · 2020
Cited alongside, same era.
Group knowledge transfer: Federated learning of large cnns at the edge
Chaoyang He, Murali Annavaram, and Salman Avestimehr · 2020
Cited alongside, same era.
Backdoor attacks and defenses in feature-partitioned collaborative learning
Yang Liu, Zhihao Yi, and Tianjian Chen · 2020
Cited alongside, same era.
Infobert: Improving robustness of language models from an information theoretic perspective
Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, and Jingjing Liu · 2020
Cited alongside, same era.
Privacy leakage of real-world vertical federated learning
Haiqin Weng, Juntao Zhang, Feng Xue, Tao Wei, Shouling Ji, and Zhiyuan Zong · 2020
Cited alongside, same era.
Improving robustness to model inversion attacks via mutual information regularization
Tianhao Wang, Yuheng Zhang, and Ruoxi Jia · 2021
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See through gradients: Image batch recovery via gradinversion
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, and Pavlo Molchanov · 2021
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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
Later among the works it cites.
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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Comprehensive analysis of privacy leakage in vertical federated learning during prediction
Xue Jiang, Xuebing Zhou, and Jens Grossklags · 2022
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Signds-fl: Local differentially private federated learning with sign-based dimension selection
Xue Jiang, Xuebing Zhou, and Jens Grossklags · 2022
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Attacking vertical collaborative learning system using adversarial dominating inputs
Qi Pang, Yuanyuan Yuan, and Shuai Wang · 2022
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Feature reconstruction attacks and countermeasures of dnn training in vertical federated learning, 2022
Peng Ye, Zhifeng Jiang, Wei Wang, Bo Li, and Baochun Li · 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
Later among the works it cites.