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109 Results
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Poster
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Thu 8:30 |
Privately Publishable Per-instance Privacy Rachel Redberg · Yu-Xiang Wang |
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Poster
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Thu 8:30 |
Differentially Private Sampling from Distributions Sofya Raskhodnikova · Satchit Sivakumar · Adam Smith · Marika Swanberg |
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Poster
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Thu 8:30 |
Fast and Memory Efficient Differentially Private-SGD via JL Projections Zhiqi Bu · Sivakanth Gopi · Janardhan Kulkarni · Yin Tat Lee · Judy Hanwen Shen · Uthaipon Tantipongpipat |
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Poster
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Thu 16:30 |
Revealing and Protecting Labels in Distributed Training Trung Dang · Om Thakkar · Swaroop Ramaswamy · Rajiv Mathews · Peter Chin · Françoise Beaufays |
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Poster
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Thu 8:30 |
User-Level Differentially Private Learning via Correlated Sampling Badih Ghazi · Ravi Kumar · Pasin Manurangsi |
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Poster
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Thu 8:30 |
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang · Samyak Gupta · Zhao Song · Kai Li · Sanjeev Arora |
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Poster
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Thu 0:30 |
Differentially Private Multi-Armed Bandits in the Shuffle Model Jay Tenenbaum · Haim Kaplan · Yishay Mansour · Uri Stemmer |
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Poster
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Tue 8:30 |
Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data Jiaxing Huang · Dayan Guan · Aoran Xiao · Shijian Lu |
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Workshop
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Mon 4:30 |
Fairness and privacy aspects of ImageNet Olga Russakovsky · Kaiyu Yang |
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Oral
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Fri 16:00 |
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang · Samyak Gupta · Zhao Song · Kai Li · Sanjeev Arora |
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Poster
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Thu 16:30 |
Fair Sequential Selection Using Supervised Learning Models Mahdi Khalili · Xueru Zhang · Mahed Abroshan |
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Workshop
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Population Level Privacy Leakage in Binary Classification wtih Label Noise Róbert Busa-Fekete · Andres Munoz Medina · Umar Syed · Sergei Vassilvitskii |