500 citations · 607 across the 14 of their papers we have counts for
14 papers
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT
Jiaqi Wang, Shenglai Zeng, Zewei Long +3
Federated learning (FL) enables multiple clients to train models collaboratively without sharing local data, which has achieved promising results in different areas, including the…
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
Zewei Long, Jiaqi Wang, Yaqing Wang +2
Federated Semi-Supervised Learning (FedSSL) has gained rising attention from both academic and industrial researchers, due to its unique characteristics of co-training machine lear…
FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning
Liwei Che, Zewei Long, Jiaqi Wang +3
Federated Learning has shown great potentials for the distributed data utilization and privacy protection. Most existing federated learning approaches focus on the supervised setti…
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
Yaqing Wang, Fenglong Ma, Haoyu Wang +2
Fake news travels at unprecedented speeds, reaches global audiences and puts users and communities at great risk via social media platforms. Deep learning based models show good pe…
Writing by Memorizing: Hierarchical Retrieval-based Medical Report Generation
Xingyi Yang, Muchao Ye, Quanzeng You +1
Medical report generation is one of the most challenging tasks in medical image analysis. Although existing approaches have achieved promising results, they either require a predef…
Fairness-aware Outlier Ensemble
Haoyu Liu, Fenglong Ma, Shibo He +2
Outlier ensemble methods have shown outstanding performance on the discovery of instances that are significantly different from the majority of the data. However, without the aware…
i-Algebra: Towards Interactive Interpretability of Deep Neural Networks
Xinyang Zhang, Ren Pang, Shouling Ji +2
Providing explanations for deep neural networks (DNNs) is essential for their use in domains wherein the interpretability of decisions is a critical prerequisite. Despite the pleth…
FedSiam: Towards Adaptive Federated Semi-Supervised Learning
Zewei Long, Liwei Che, Yaqing Wang +5
Federated learning (FL) has emerged as an effective technique to co-training machine learning models without actually sharing data and leaking privacy. However, most existing FL me…
Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
Junyu Luo, Zifei Zheng, Hanzhong Ye +5
Patients with low health literacy usually have difficulty understanding medical jargon and the complex structure of professional medical language. Although some studies are propose…
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
Chacha Chen, Junjie Liang, Fenglong Ma +3
Successful health risk prediction demands accuracy and reliability of the model. Existing predictive models mainly depend on mining electronic health records (EHR) with advanced de…
Efficient Knowledge Graph Validation via Cross-Graph Representation Learning
Yaqing Wang, Fenglong Ma, Jing Gao
Recent advances in information extraction have motivated the automatic construction of huge Knowledge Graphs (KGs) by mining from large-scale text corpus. However, noisy facts are…
Weak Supervision for Fake News Detection via Reinforcement Learning
Yaqing Wang, Weifeng Yang, Fenglong Ma +4
Today social media has become the primary source for news. Via social media platforms, fake news travel at unprecedented speeds, reach global audiences and put users and communitie…
Long-Term Memory Networks for Question Answering
Fenglong Ma, Radha Chitta, Saurabh Kataria +4
Question answering is an important and difficult task in the natural language processing domain, because many basic natural language processing tasks can be cast into a question an…
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks
Fenglong Ma, Radha Chitta, Jing Zhou +3
Predicting the future health information of patients from the historical Electronic Health Records (EHR) is a core research task in the development of personalized healthcare. Pati…