Yun Shen

Partially supervised graph embedding for positive unlabelled feature selection

2016 · International Joint Conference on Artificial Intelligence

Selecting discriminative features in positive unlabelled (PU) learning tasks is a challenging problem due to lack of negative class information. Traditional supervised and semi-supervised feature selection methods are not able to be applied directly in …

Model Stealing Attacks Against Inductive Graph Neural Networks

2022 · 2022 IEEE Symposium on Security and Privacy (SP)

Many real-world data come in the form of graphs. Graph neural networks (GNNs), a new family of machine learning (ML) models, have been proposed to fully leverage graph data to build powerful applications. In particular, …

Backdoor Attacks Against Dataset Distillation

2023

Dataset distillation has emerged as a prominent technique to improve data efficiency when training machine learning models. It encapsulates the knowledge from a large dataset into a smaller synthetic dataset. A model trained on this …

FAKEPCD: Fake Point Cloud Detection via Source Attribution

2024

To prevent the mischievous use of synthetic (fake) point clouds produced by generative models, we pioneer the study of detecting point cloud authenticity and attributing them to their sources. We propose an attribution framework FakePCD …