PrivFL: Practical privacy-preserving federated regressions on high-dimensional data over mobile networks

K Mandal, G Gong - Proceedings of the 2019 ACM SIGSAC Conference …, 2019 - dl.acm.org
Federated Learning (FL) enables a large number of users to jointly learn a shared machine
learning (ML) model, coordinated by a centralized server, where the data is distributed …
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PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks

K Mandal, G Gong - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Federated Learning (FL) enables a large number of users to jointly learn a shared machine
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PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks

K Mandal, G Gong - Cryptology ePrint Archive, 2019 - eprint.iacr.org
Federated Learning (FL) enables a large number of users to jointly learn a shared machine
learning (ML) model, coordinated by a centralized server, where the data is distributed …

PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks

K Mandal, G Gong - arXiv preprint arXiv:2004.02264, 2020 - arxiv.org
Federated Learning (FL) enables a large number of users to jointly learn a shared machine
learning (ML) model, coordinated by a centralized server, where the data is distributed …
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[PDF][PDF] PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks

K Mandal, G Gong - cacr.uwaterloo.ca
Federated Learning (FL) enables a large number of users to jointly learn a shared machine
learning (ML) model, coordinated by a centralized server, where the data is distributed …