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We introduce a collaborative learning framework allowing multiple parties having different sets of attributes about the same user to jointly build models without exposing their raw data or model parameters.
On data banks and privacy homomorphisms
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Privacy preserving association rule mining in vertically partitioned data
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Privacy-preserving multivariate statistical analysis: Linear regression and classification
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Privacy-preserving classification of vertically partitioned data via random kernels
Mangasarian, O. L., E. W. Wild, G. M. Fung · 2008
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NUS-WIDE: A real-world web image database from National University of Singapore
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MNIST handwritten digit database
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Large scale distributed deep networks
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Stochastic first-and zeroth-order methods for nonconvex stochastic programming
Ghadimi, S., G. Lan · 2013
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Arock: an algorithmic framework for asynchronous parallel coordinate updates
Peng, Z., Y. Xu, M. Yan, et al · 2015
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Privacy-preserving deep learning
Shokri, R., V. Shmatikov · 2015
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REGULATION (EU) 2016/679 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation)
EU · 2016
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Federated learning of deep networks using model averaging
McMahan, H. B., E. Moore, D. Ramage, et al · 2016
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Distributed coordinate descent method for learning with big data
Richtárik, P., M. Takáč · 2016
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Mimic-iii, a freely accessible critical care database
Johnson, A. E., T. J. Pollard, L. Shen, et al · 2016
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Exploiting unintended feature leakage in collaborative learning
Melis, L., C. Song, E. D. Cristofaro, et al · 2018
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Federated machine learning: Concept and applications
Yang, Q., Y. Liu, T. Chen, et al · 2019
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Fdml: A collaborative machine learning framework for distributed features
Hu, Y., D. Niu, J. Yang, et al · 2019
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Learning privately over distributed features: An ADMM sharing approach
Hu, Y., P. Liu, L. Kong, et al · 2019
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Secureboost: A lossless federated learning framework
Cheng, K., T. Fan, Y. Jin, et al · 2019
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A distributed block coordinate descent method for training l1regularized linear classifiers
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Deep models under the gan: Information leakage from collaborative deep learning
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Multitask learning and benchmarking with clinical time series data
Harutyunyan, H., H. Khachatrian, D. C. Kale, et al · 2017
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Distributed ridge regression with feature partitioning
Gratton, C., V. D., R. Arablouei, et al · 2018
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Secure federated transfer learning
Liu, Y., T. Chen, Q. Yang · 2018
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Parallel restarted sgd with faster convergence and less communication: Demystifying why model averaging works for deep learning
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On the convergence of FedAvg on non-iid data
Li, X., K. Huang, W. Yang, et al · 2019
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Deep leakage from gradients
Zhu, L., Z. Liu, S. Han · 2019
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Federated optimization for heterogeneous networks
Li, T., A. K. Sahu, M. Zaheer, et al · 2019
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Practical federated gradient boosting decision trees
Li, Q., Z. Wen, B. He · 2020
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