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68 Results
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Poster
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Tue 14:00 |
What You See is What You Get: Principled Deep Learning via Distributional Generalization Bogdan Kulynych · Yao-Yuan Yang · Yaodong Yu · Jarosław Błasiok · Preetum Nakkiran |
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Poster
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Thu 14:00 |
Sampling from Log-Concave Distributions with Infinity-Distance Guarantees Oren Mangoubi · Nisheeth Vishnoi |
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Poster
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Thu 9:00 |
Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions Omri Ben-Eliezer · Dan Mikulincer · Ilias Zadik |
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Poster
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Thu 9:00 |
Near-Optimal Correlation Clustering with Privacy Vincent Cohen-Addad · Chenglin Fan · Silvio Lattanzi · Slobodan Mitrovic · Ashkan Norouzi-Fard · Nikos Parotsidis · Jakub Tarnawski |
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Poster
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Thu 9:00 |
Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams Sergey Denisov · H. Brendan McMahan · John Rush · Adam Smith · Abhradeep Guha Thakurta |
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Poster
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Tue 14:00 |
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation Kristian Georgiev · Samuel Hopkins |
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Poster
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Thu 9:00 |
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li · Daogao Liu · Tatsunori Hashimoto · Huseyin A. Inan · Janardhan Kulkarni · Yin-Tat Lee · Abhradeep Guha Thakurta |
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Poster
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Wed 9:00 |
A General Framework for Auditing Differentially Private Machine Learning Fred Lu · Joseph Munoz · Maya Fuchs · Tyler LeBlond · Elliott Zaresky-Williams · Edward Raff · Francis Ferraro · Brian Testa |