Geographic Spines in the 2020 Census Disclosure Avoidance System. (arXiv:2203.16654v2 [cs.CR] UPDATED)
The 2020 Census Disclosure Avoidance System (DAS) is a formally private mechanism that first adds independent noise to cross tabulations...
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Geographic Spines in the 2020 Census Disclosure Avoidance System. (arXiv:2203.16654v2 [cs.CR] UPDATED)
The 2020 Census Disclosure Avoidance System (DAS) is a formally private mechanism that first adds independent noise to cross tabulations...
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. (arXiv:2205.08532v4 [cs.DS] UPDATED)
We prove new lower bounds for statistical estimation tasks under the constraint of $(varepsilon, delta)$-differential privacy. First, we provide tight...
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. (arXiv:2205.08532v4 [cs.DS] UPDATED)
We prove new lower bounds for statistical estimation tasks under the constraint of $(varepsilon, delta)$-differential privacy. First, we provide tight...
Revisiting LiDAR Spoofing Attack Capabilities against Object Detection: Improvements, Measurement, and New Attack. (arXiv:2303.10555v1 [cs.CR])
LiDAR (Light Detection And Ranging) is an indispensable sensor for precise long- and wide-range 3D sensing, which directly benefited the...
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma. (arXiv:2205.08532v4 [cs.DS] UPDATED)
We prove new lower bounds for statistical estimation tasks under the constraint of $(varepsilon, delta)$-differential privacy. First, we provide tight...
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. (arXiv:2205.11765v2 [cs.LG] UPDATED)
We propose Byzantine-robust federated learning protocols with nearly optimal statistical rates. In contrast to prior work, our proposed protocols improve...
AdaptGuard: Defending Against Universal Attacks for Model Adaptation. (arXiv:2303.10594v1 [cs.CR])
Model adaptation aims at solving the domain transfer problem under the constraint of only accessing the pretrained source models. With...
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. (arXiv:2205.11765v2 [cs.LG] UPDATED)
We propose Byzantine-robust federated learning protocols with nearly optimal statistical rates. In contrast to prior work, our proposed protocols improve...
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. (arXiv:2205.11765v2 [cs.LG] UPDATED)
We propose Byzantine-robust federated learning protocols with nearly optimal statistical rates. In contrast to prior work, our proposed protocols improve...