8 citations · 13 across the 5 of their papers we have counts for
5 papers
PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training
Sichun Luo, Yuanzhang Xiao, Xinyi Zhang +3
Federated recommendation systems employ federated learning techniques to safeguard user privacy by transmitting model parameters instead of raw user data between user devices and t…
HySAGE: A Hybrid Static and Adaptive Graph Embedding Network for Context-Drifting Recommendations
Sichun Luo, Xinyi Zhang, Yuanzhang Xiao +1
The recent popularity of edge devices and Artificial Intelligent of Things (AIoT) has driven a new wave of contextual recommendations, such as location based Point of Interest (PoI…
Defense Strategies Toward Model Poisoning Attacks in Federated Learning: A Survey
Zhilin Wang, Qiao Kang, Xinyi Zhang +1
Advances in distributed machine learning can empower future communications and networking. The emergence of federated learning (FL) has provided an efficient framework for distribu…
Speech Technology for Everyone: Automatic Speech Recognition for Non-Native English with Transfer Learning
Toshiko Shibano, Xinyi Zhang, Mia Taige Li +3
To address the performance gap of English ASR models on L2 English speakers, we evaluate fine-tuning of pretrained wav2vec 2.0 models (Baevski et al., 2020; Xu et al., 2021) on L2-…
Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack
Xinyi Zhang, Chengfang Fang, Jie Shi
Model extraction increasingly attracts research attentions as keeping commercial AI models private can retain a competitive advantage. In some scenarios, AI models are trained prop…