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This paper studies multiparty learning, aiming to learn a model using the private data of different participants.
How to generate and exchange secrets
Andrew Chi-Chih Yao · 1986
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k-anonymity: A model for protecting privacy
Latanya Sweeney · 2002
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Secure multiparty computation for privacy preserving data mining
Yehida Lindell · 2005
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Pattern recognition and machine learning
Christopher M Bishop and Nasser M Nasrabadi · 2006
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Differential privacy: A survey of results
Cynthia Dwork · 2008
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Multiparty differential privacy via aggregation of locally trained classifiers
Manas Pathak, Shantanu Rane, and Bhiksha Raj · 2010
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A firm foundation for private data analysis
Cynthia Dwork · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Efficient optimization of performance measures by classifier adaptation
Nan Li, Ivor W Tsang, and Zhi-Hua Zhou · 2012
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A differentially private stochastic gradient descent algorithm for multiparty classification
Arun Rajkumar and Shivani Agarwal · 2012
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Ensemble methods: foundations and algorithms
Zhi-Hua Zhou · 2012
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The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al · 2014
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Privacy-preserving deep learning
Reza Shokri and Vitaly Shmatikov · 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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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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H Brendan McMahan, Eider Moore, Daniel Ramage, and Blaise Agüera y Arcas · 2016
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Zhi Hua Zhou · 2016
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Payman Mohassel and Peter Rindal · 2018
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Rsa: Byzantine-robust stochastic aggregation methods for distributed learning from heterogeneous datasets
Liping Li, Wei Xu, Tianyi Chen, Georgios B Giannakis, and Qing Ling · 2019
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Machine learning in medicine
Alvin Rajkomar, Jeffrey Dean, and Isaac Kohane · 2019
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Heterogeneous model reuse via optimizing multiparty multiclass margin
Xi Zhu Wu, Song Liu, and Zhi Hua Zhou · 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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Boosting-Based Reliable Model Reuse
Yao-Xiang Ding, Zhi-Hua Zhou, Sinno Jialin Pan, and Masashi Sugiyama · 2020
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Differentially private normalizing flows for privacy-preserving density estimation
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Swarm learning for decentralized and confidential clinical machine learning
Stefanie Warnat-Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N Ahmad Aziz, et al · 2021
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Model reuse with reduced kernel mean embedding specification
X. Wu, W. Xu, S. Liu, and Z. Zhou · 2023
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