Search Results for author:
Found 6 papers, 2 papers with code
COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks
In this work, we propose the first robustness certification framework COMMIT certify robustness of multi-sensor fusion systems against semantic attacks.
Physically Realizable Natural-Looking Clothing Textures Evade Person Detectors via 3D Modeling
In order to craft natural-looking adversarial clothes that can evade person detectors at multiple viewing angles, we propose adversarial camouflage textures (AdvCaT) that resemble one kind of the typical textures of daily clothes, camouflage textures.
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees
In this paper, we propose PerAda, a parameter-efficient pFL framework that reduces communication and computational costs and exhibits superior generalization performance, especially under test-time distribution shifts.
Distributed Robust Principal Component Analysis
We study the robust principal component analysis (RPCA) problem in a distributed setting.
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data
However, due to the heterogeneous nature of local data, it is challenging to optimize or even define fairness of the trained global model for the agents.
TPC: Transformation-Specific Smoothing for Point Cloud Models
In this paper, we propose a transformation-specific smoothing framework TPC, which provides tight and scalable robustness guarantees for point cloud models against semantic transformation attacks.
