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Do Gradient Inversion Attacks Make Federated Learning Unsafe?

A. Hatamizadeh, H. Yin, P. Molchanov, A. Myronenko, W. Li, P. Dogra, A. Feng, M. Flores, J. Kautz, D. Xu, and H. Roth. CoRR, (2022)

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Masyar Monazahian

Walter Monar

Hanno Lorenz Monauni

Anneliese Monat

Carmen Monasterio

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Do Gradient Inversion Attacks Make Federated Learning Unsafe?A. Hatamizadeh, H. Yin, P. Molchanov, A. Myronenko, W. Li, P. Dogra, A. Feng, M. Flores, J. Kautz, D. Xu and 1 other author(s). IEEE Trans. Medical Imaging, 42 (7): 2044-2056 (2023)A large language model for electronic health records.X. Yang, A. Chen, N. Pournejatian, H. Shin, K. Smith, C. Parisien, C. Compas, C. Martin, A. Costa, M. Flores and 9 other author(s). npj Digit. Medicine, (2022)Federated learning improves site performance in multicenter deep learning without data sharing.K. Sarma, S. Harmon, T. Sanford, H. Roth, Z. Xu, J. Tetreault, D. Xu, M. Flores, A. Raman, R. Kulkarni and 9 other author(s). J. Am. Medical Informatics Assoc., 28 (6): 1259-1264 (2021)Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Need.C. Peng, X. Yang, A. Chen, Z. Yu, K. Smith, A. Costa, M. Flores, J. Bian, and Y. Wu. CoRR, (2023)GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records.X. Yang, N. Pournejatian, H. Shin, K. Smith, C. Parisien, C. Compas, C. Martin, M. Flores, Y. Zhang, T. Magoc and 7 other author(s). CoRR, (2022)Do Gradient Inversion Attacks Make Federated Learning Unsafe?A. Hatamizadeh, H. Yin, P. Molchanov, A. Myronenko, W. Li, P. Dogra, A. Feng, M. Flores, J. Kautz, D. Xu and 1 other author(s). CoRR, (2022)Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning.V. Gupta, H. Roth, V. Buch, M. Rockenbach, R. White, D. Yang, O. Laur, B. Ghoshhajra, I. Dayan, D. Xu and 2 other author(s). CoRR, (2020)A study of generative large language model for medical research and healthcare.C. Peng, X. Yang, A. Chen, K. Smith, N. Pournejatian, A. Costa, C. Martin, M. Flores, Y. Zhang, T. Magoc and 9 other author(s). npj Digit. Medicine, (2023)Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application.V. Gupta, C. Taylor, S. Bonnet, L. Prevedello, J. Hawley, R. White, M. Flores, and B. Erdal. CoRR, (2020)Deep Learning Based Automatic Detection of Adequately Positioned Mammograms.V. Gupta, C. Taylor, S. Bonnet, L. Prevedello, J. Hawley, R. White, M. Flores, and B. Erdal. DART/FAIR@MICCAI, volume 12968 of Lecture Notes in Computer Science, page 239-250. Springer, (2021)

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Disambiguation of "Flores, Mona G."

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Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Please choose a person to relate this publication to

Masyar Monazahian

Walter Monar

Hanno Lorenz Monauni

Anneliese Monat

Carmen Monasterio

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Flores, Mona G."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Do Gradient Inversion Attacks Make Federated Learning Unsafe?

Please choose a person to relate this publication to

Masyar Monazahian

Walter Monar

Hanno Lorenz Monauni

Anneliese Monat

Carmen Monasterio

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
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Do Gradient Inversion Attacks Make Federated Learning Unsafe?