90 citations · 563 across the 40 of their papers we have counts for
8 papers · 1 filter
Tackling Data Heterogeneity in Federated Learning with Class Prototypes
Yutong Dai, Zeyuan Chen, Junnan Li +3
Data heterogeneity across clients in federated learning (FL) settings is a widely acknowledged challenge. In response, personalized federated learning (PFL) emerged as a framework…
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples
Shengshan Hu, Junwei Zhang, Wei Liu +5
Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While v…
Transferable Unlearnable Examples
Jie Ren, Han Xu, Yuxuan Wan +3
With more people publishing their personal data online, unauthorized data usage has become a serious concern. The unlearnable strategies have been introduced to prevent third parti…
Data-Free Adversarial Knowledge Distillation for Graph Neural Networks
Yuanxin Zhuang, Lingjuan Lyu, Chuan Shi +2
Graph neural networks (GNNs) have been widely used in modeling graph structured data, owing to its impressive performance in a wide range of practical applications. Recently, knowl…
Membership Inference via Backdooring
Hongsheng Hu, Zoran Salcic, Gillian Dobbie +3
Recently issued data privacy regulations like GDPR (General Data Protection Regulation) grant individuals the right to be forgotten. In the context of machine learning, this requir…
Secure Embedding Aggregation for Federated Representation Learning
Jiaxiang Tang, Jinbao Zhu, Songze Li +1
We consider a federated representation learning framework, where with the assistance of a central server, a group of distributed clients train collaboratively over their privat…