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246 Results
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Poster
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Tue 13:00 |
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn · Boi Faltings |
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Poster
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Tue 9:00 |
Context Aware Local Differential Privacy Jayadev Acharya · Kallista Bonawitz · Peter Kairouz · Daniel Ramage · Ziteng Sun |
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Poster
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Wed 12:00 |
Radioactive data: tracing through training Alexandre Sablayrolles · Douze Matthijs · Cordelia Schmid · Herve Jegou |
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Poster
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Thu 8:00 |
Certified Data Removal from Machine Learning Models Chuan Guo · Tom Goldstein · Awni Hannun · Laurens van der Maaten |
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Poster
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Thu 6:00 |
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion Qinqing Zheng · Jinshuo Dong · Qi Long · Weijie Su |
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Poster
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Thu 7:00 |
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data Di Wang · Hanshen Xiao · Srinivas Devadas · Jinhui Xu |
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Poster
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Wed 11:00 |
From Local SGD to Local Fixed-Point Methods for Federated Learning Grigory Malinovsky · Dmitry Kovalev · Elnur Gasanov · Laurent CONDAT · Peter Richtarik |
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Poster
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Thu 7:00 |
Optimal Differential Privacy Composition for Exponential Mechanisms Jinshuo Dong · David Durfee · Ryan Rogers |
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Poster
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Tue 7:00 |
Fast and Private Submodular and -Submodular Functions Maximization with Matroid Constraints Akbar Rafiey · Yuichi Yoshida |
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Poster
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Thu 6:00 |
New Oracle-Efficient Algorithms for Private Synthetic Data Release Giuseppe Vietri · Grace Tian · Mark Bun · Thomas Steinke · Steven Wu |
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Poster
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Wed 5:00 |
InstaHide: Instance-hiding Schemes for Private Distributed Learning Yangsibo Huang · Zhao Song · Kai Li · Sanjeev Arora |
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Poster
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Tue 7:00 |
Fair Learning with Private Demographic Data Hussein Mozannar · Mesrob Ohannessian · Nati Srebro |