78 citations · 139 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
Towards Fair Classification against Poisoning Attacks
Han Xu, Xiaorui Liu, Yuxuan Wan +1
Fair classification aims to stress the classification models to achieve the equality (treatment or prediction quality) among different sensitive groups. However, fair classificatio…
Probabilistic Categorical Adversarial Attack & Adversarial Training
Han Xu, Pengfei He, Jie Ren +4
The existence of adversarial examples brings huge concern for people to apply Deep Neural Networks (DNNs) in safety-critical tasks. However, how to generate adversarial examples wi…
PCDF: A Parallel-Computing Distributed Framework for Sponsored Search Advertising Serving
Han Xu, Hao Qi, Kunyao Wang +8
Traditional online advertising systems for sponsored search follow a cascade paradigm with retrieval, pre-ranking,ranking, respectively. Constrained by strict requirements on onlin…
Defense Against Gradient Leakage Attacks via Learning to Obscure Data
Yuxuan Wan, Han Xu, Xiaorui Liu +3
Federated learning is considered as an effective privacy-preserving learning mechanism that separates the client's data and model training process. However, federated learning is s…
Enhancing Adversarial Training with Feature Separability
Yaxin Li, Xiaorui Liu, Han Xu +2
Deep Neural Network (DNN) are vulnerable to adversarial attacks. As a countermeasure, adversarial training aims to achieve robustness based on the min-max optimization problem and…