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Poster
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Fri 8:30 |
An Uncertainty Principle is a Price of Privacy-Preserving Microdata John Abowd · Robert Ashmead · Ryan Cumings-Menon · Simson Garfinkel · Daniel Kifer · Philip Leclerc · William Sexton · Ashley Simpson · Christine Task · Pavel Zhuravlev |
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Workshop
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Privacy-Aware Rejection Sampling Jordan Awan · Vinayak Rao |
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Workshop
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Tue 12:15 |
Privacy-Aware Rejection Sampling Jordan Awan · Vinayak Rao |
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Workshop
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Tue 2:45 |
SoK: Privacy-preserving Clustering (Extended Abstract) Helen Möllering · Hossein Yalame · Thomas Schneider · Aditya Hegde |
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Affinity Workshop
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Privacy-Preseving Federated Multi-Task Linear Regression: A One-shot Linear Mixing Approach Inspired by Graph Regularization Harlin Lee |
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Workshop
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SoK: Privacy-preserving Clustering (Extended Abstract) Helen Möllering · Hossein Yalame · Aditya Hegde · Thomas Schneider |
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Workshop
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Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy Rahul Singh |
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Workshop
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Label Private Deep Learning Training based on Secure Multiparty Computation and Differential Privacy Sen Yuan · Milan Shen · Ilya Mironov · Anderson Nascimento |
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Workshop
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ABY2.0: New Efficient Primitives for STPC with Applications to Privacy in Machine Learning (Extended Abstract) Arpita Patra · Hossein Yalame · Thomas Schneider · Ajith Suresh |
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Workshop
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Feature-level privacy loss modelling in differentially private machine learning Dmitrii Usynin · Alexander Ziller · Moritz Knolle · Daniel Rueckert · Georgios Kaissis |
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Workshop
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Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour · Igor Shilov · Alexandre Sablayrolles · Karthik Prasad · Mani Malek Esmaeili · John Nguyen · Sayan Ghosh · Akash Bharadwaj · Jessica Zhao · Graham Cormode · Ilya Mironov |
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Workshop
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Differential Privacy via Group Shuffling Amir Mohammad Abouei · Clement Canonne |