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Vicious Classifiers: Data Reconstruction Attack at Inference Time


Dec 08, 2022
Mohammad Malekzadeh, Deniz Gunduz

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* 14 pages 

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Centaur: Federated Learning for Constrained Edge Devices


Nov 12, 2022
Fan Mo, Mohammad Malekzadeh, Soumyajit Chatterjee, Fahim Kawsar, Akhil Mathur

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* 15 pages, 10 figures 

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Efficient Hyperparameter Optimization for Differentially Private Deep Learning


Aug 09, 2021
Aman Priyanshu, Rakshit Naidu, Fatemehsadat Mireshghallah, Mohammad Malekzadeh

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* 4+1 pages, 4 figures, 1 table 

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Quantifying Information Leakage from Gradients


May 28, 2021
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

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* 18 pages, 9 figures 

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Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs


May 25, 2021
Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz

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Dopamine: Differentially Private Federated Learning on Medical Data


Jan 29, 2021
Mohammad Malekzadeh, Burak Hasircioglu, Nitish Mital, Kunal Katarya, Mehmet Emre Ozfatura, Deniz Gündüz

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* The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21) 

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Dopamine: Differentially Private Secure Federated Learning on Medical Data


Jan 27, 2021
Mohammad Malekzadeh, Burak Hasircioglu, Nitish Mital, Kunal Katarya, Mehmet Emre Ozfatura, Deniz Gündüz

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* The Second AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-21) 

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Layer-wise Characterization of Latent Information Leakage in Federated Learning


Oct 17, 2020
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

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* 17 pages, 11 figures 

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Running Neural Networks on the NIC


Sep 04, 2020
Giuseppe Siracusano, Salvator Galea, Davide Sanvito, Mohammad Malekzadeh, Hamed Haddadi, Gianni Antichi, Roberto Bifulco

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