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06/05/2023
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
Malicious server (MS) attacks have enabled the scaling of data stealing ...
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10/27/2022
Private and Reliable Neural Network Inference
Reliable neural networks (NNs) provide important inference-time reliabil...
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10/13/2022
FARE: Provably Fair Representation Learning
Fair representation learning (FRL) is a popular class of methods aiming ...
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04/30/2022
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
State-of-the-art neural network verifiers are fundamentally based on one...
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02/17/2022
LAMP: Extracting Text from Gradients with Language Model Priors
Recent work shows that sensitive user data can be reconstructed from gra...
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02/25/2021
Towards Robust Graph Contrastive Learning
We study the problem of adversarially robust self-supervised learning on...
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02/12/2021
Certified Defenses: Why Tighter Relaxations May Hurt Training?
Certified defenses based on convex relaxations are an established techni...
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11/03/2018