Privacy-Preserving Federated Recurrent Neural Networks von Sav, Sinem, Diaa, Abdulrahman, Pyrgelis, Apostolos, Bossuat, Jean-Philippe, Hubaux, Jean-Pierre

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Optimizing Adaptive Attacks against Content Watermarks for Language Models von Diaa, Abdulrahman, Aremu, Toluwani, Lukas, Nils

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FastLloyd: Federated, Accurate, Secure, and Tunable $k$-Means Clustering with Differential Privacy von Diaa, Abdulrahman, Humphries, Thomas, Kerschbaum, Florian

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HE is all you need: Compressing FHE Ciphertexts using Additive HE von Mahdavi, Rasoul Akhavan, Diaa, Abdulrahman, Kerschbaum, Florian

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Leveraging Optimization for Adaptive Attacks on Image Watermarks von Lukas, Nils, Diaa, Abdulrahman, Fenaux, Lucas, Kerschbaum, Florian

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Optimizing Adaptive Attacks against Content Watermarks for Language Models von Abdulrahman Diaa, Aremu, Toluwani, Lukas, Nils

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HE is all you need: Compressing FHE Ciphertexts using Additive HE von Rasoul Akhavan Mahdavi, Abdulrahman Diaa, Kerschbaum, Florian

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FastLloyd: Federated, Accurate, Secure, and Tunable \(k\)-Means Clustering with Differential Privacy von Abdulrahman Diaa, Humphries, Thomas, Kerschbaum, Florian

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Splitting neural networks on multiple edge devices to train on vertically distributed data von Abouzeid, Mohamed, Diaa, AbdulRahman, Mohamed, Osama Taha

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Privacy-Preserving Federated Recurrent Neural Networks von Sav, Sinem, Diaa, Abdulrahman, Pyrgelis, Apostolos, Bossuat, Jean-Philippe, Hubaux, Jean-Pierre

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Leveraging Optimization for Adaptive Attacks on Image Watermarks von Lukas, Nils, Abdulrahman Diaa, Lucas Fenaux, Kerschbaum, Florian

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Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions von Diaa, Abdulrahman, Fenaux, Lucas, Humphries, Thomas, Dietz, Marian, Ebrahimianghazani, Faezeh, Kacsmar, Bailey, Li, Xinda, Lukas, Nils, Mahdavi, Rasoul Akhavan, Oya, Simon, Amjadian, Ehsan, Kerschbaum, Florian

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SPLITTING NEURAL NETWORKS ON MULTIPLE EDGE DEVICES TO TRAIN ON VERTICALLY DISTRIBUTED DATA von Abouzeid, Mohamed, Diaa, AbdulRahman, Mohamed, Osama Taha

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Privacy-Preserving Federated Recurrent Neural Networks von Sav, Sinem, Abdulrahman Diaa, Pyrgelis, Apostolos, Jean-Philippe Bossuat, Hubaux, Jean-Pierre

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Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions von Abdulrahman Diaa, Lucas Fenaux, Humphries, Thomas, Dietz, Marian, Ebrahimianghazani, Faezeh, Bailey Kacsmar, Li, Xinda, Lukas, Nils, Rasoul Akhavan Mahdavi, Simon, Oya, Amjadian, Ehsan, Kerschbaum, Florian

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MARKET BASKET ANALYSIS FOR INFANT HYBRID TECHNOLOGY DETECTION von Abouzeid, Mohamed, Osama, Ahmed, Aziz, Amr Abdel, Toma, Marianne, Moussa, Yaseen, Diaa, Abdulrahman, Todd, Stephen J, Mohamed, Osama Taha

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DATA-DRIVEN INDEX FOR IDENTIFICATION AND RANKING OF COMPANIES FOR A SELECTED TECHNOLOGY von Taha Mohamed Abdelbaky, Osama, Abouzeid, Mohamed Ahmed Amr, Moussa, Yaseen Tamer Refaie, Diaa Eldin, Abdulrahman Mohamed

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Cytotoxic and Antimicrobial Compounds from the Marine-Derived Fungus, Penicillium Species von Youssef, Diaa T A, Alahdal, Abdulrahman M

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A Comparative Numerical Study of the Symmetry Chaotic Jerk System with a Hyperbolic Sine Function via Two Different Methods von Alzahrani, Abdulrahman B. M., Abdoon, Mohamed A., Elbadri, Mohamed, Berir, Mohammed, Elgezouli, Diaa Eldin

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Optimizing Edge Detection Efficiency with a Grünwald–Letnikov Fractional Network von Elgezouli, Diaa Eldin, Alzahrani, Abdulrahman B. M

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