Different Deep Learning Based Classification Models for COVID-19 CT-Scans and Lesion Segmentation Through the cGAN-UNet Hybrid Method von Ngong, Ivoline C., Baykan, Nurdan Akhan

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Differentially Private Learning Needs Better Model Initialization and Self-Distillation von Ngong, Ivoline C, Near, Joseph P, Mireshghallah, Niloofar

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Evaluating the Usability of Differential Privacy Tools with Data Practitioners von Ngong, Ivoline C, Stenger, Brad, Near, Joseph P, Feng, Yuanyuan

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OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols von Ngong, Ivoline C, Gibson, Nicholas, Near, Joseph P

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Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers von Maughan, Krystal, Ngong, Ivoline C, Near, Joseph P

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Backpropagation Clipping for Deep Learning with Differential Privacy von Stevens, Timothy, Ngong, Ivoline C, Darais, David, Hirsch, Calvin, Slater, David, Near, Joseph P

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Towards Auditability for Fairness in Deep Learning von Ngong, Ivoline C, Maughan, Krystal, Near, Joseph P

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SoK: Usability Studies in Differential Privacy von Dibia, Onyinye, Stenger, Brad, Baldasty, Steven, Bates, Mako, Ngong, Ivoline C, Feng, Yuanyuan, Near, Joseph P

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Differentially Private Learning Needs Better Model Initialization and Self-Distillation von Ngong, Ivoline C, Near, Joseph P, Mireshghallah, Niloofar

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Evaluating the Usability of Differential Privacy Tools with Data Practitioners von Ngong, Ivoline C, Stenger, Brad, Near, Joseph P, Feng, Yuanyuan

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OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols von Ngong, Ivoline C, Gibson, Nicholas, Near, Joseph P

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Feature Extraction Methods for Predicting the Prevalence of Heart Disease von Ngong, Ivoline C., Baykan, Nurdan Akhan

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SoK: Usability Studies in Differential Privacy von Dibia, Onyinye, Stenger, Brad, Baldasty, Steven, Bates, Mako, Ngong, Ivoline C, Feng, Yuanyuan, Near, Joseph P

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Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers von Maughan, Krystal, Ngong, Ivoline C, Near, Joseph P

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Towards Auditability for Fairness in Deep Learning von Ngong, Ivoline C, Maughan, Krystal, Near, Joseph P

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Backpropagation Clipping for Deep Learning with Differential Privacy von Stevens, Timothy, Ngong, Ivoline C, Darais, David, Hirsch, Calvin, Slater, David, Near, Joseph P

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"I inherently just trust that it works": Investigating Mental Models of Open-Source Libraries for Differential Privacy von Song, Patrick, Sarathy, Jayshree, Shoemate, Michael, Vadhan, Salil

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