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20212024
most citedGeneral Cutting Planes for Bound-Propagation-Based Neural Network Verification

33 citations · 42 across the 8 of their papers we have counts for

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cs.LG2024

COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks

Zijian Huang, Wenda Chu, Linyi Li +2

Multi-sensor fusion systems (MSFs) play a vital role as the perception module in modern autonomous vehicles (AVs). Therefore, ensuring their robustness against common and realistic…

cs.LG20234 cited

Delving into the Adversarial Robustness of Federated Learning

Jie Zhang, Bo Li, Chen Chen +4

In Federated Learning (FL), models are as fragile as centrally trained models against adversarial examples. However, the adversarial robustness of federated learning remains largel…

cs.LG202233 cited

General Cutting Planes for Bound-Propagation-Based Neural Network Verification

Huan Zhang, Shiqi Wang, Kaidi Xu +5

Bound propagation methods, when combined with branch and bound, are among the most effective methods to formally verify properties of deep neural networks such as correctness, robu…

cs.LG2022

Game of Trojans: A Submodular Byzantine Approach

Dinuka Sahabandu, Arezoo Rajabi, Luyao Niu +3

Machine learning models in the wild have been shown to be vulnerable to Trojan attacks during training. Although many detection mechanisms have been proposed, strong adaptive attac…

cs.LG2022

How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirection

Mantas Mazeika, Bo Li, David Forsyth

Model stealing attacks present a dilemma for public machine learning APIs. To protect financial investments, companies may be forced to withhold important information about their m…