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Workshop
Mean Estimation with User-level Privacy under Data Heterogeneity
Rachel Cummings · Vitaly Feldman · Audra McMillan · Kunal Talwar
Workshop
ABY2.0: New Efficient Primitives for STPC with Applications to Privacy in Machine Learning (Extended Abstract)
Arpita Patra · Hossein Yalame · Thomas Schneider · Ajith Suresh
Workshop
Differential Privacy via Group Shuffling
Amir Mohammad Abouei · Clement Canonne
Workshop
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy
Rahul Singh
Workshop
FeO2: Federated Learning with Opt-Out Differential Privacy
Nasser Aldaghri · Hessam Mahdavifar · Ahmad Beirami
Poster
Thu 8:30 Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent
Rishav Chourasia · Jiayuan Ye · Reza Shokri
Affinity Workshop
Tue 11:30 On the Pitfalls of Label Differential Privacy
Andres Munoz Medina · Róbert Busa-Fekete · Umar Syed · Sergei Vassilvitskii
Workshop
Mon 14:00 Ethics:: Addressing Privacy Threats from Machine Learning
Mary Anne Smart
Workshop
Sample-and-threshold differential privacy: Histograms and applications
Graham Cormode
Workshop
Tight Accounting in the Shuffle Model of Differential Privacy
Antti Koskela · Mikko Heikkilä · Antti Honkela
Workshop
Communication Efficient Federated Learning with Secure Aggregation and Differential Privacy
Wei-Ning Chen · Christopher Choquette-Choo · Peter Kairouz
Workshop
Label Private Deep Learning Training based on Secure Multiparty Computation and Differential Privacy
Sen Yuan · Milan Shen · Ilya Mironov · Anderson Nascimento