118 citations · 236 across the 20 of their papers we have counts for
13 papers · 1 filter
Towards Collaborative Fairness in Federated Learning Under Imbalanced Covariate Shift
Tianrun Yu, Jiaqi Wang, Haoyu Wang +4
Collaborative fairness is a crucial challenge in federated learning. However, existing approaches often overlook a practical yet complex form of heterogeneity: imbalanced covariate…
FEDKIM: Adaptive Federated Knowledge Injection into Medical Foundation Models
Xiaochen Wang, Jiaqi Wang, Houping Xiao +2
Foundation models have demonstrated remarkable capabilities in handling diverse modalities and tasks, outperforming conventional artificial intelligence (AI) approaches that are hi…
Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models
Yuan Zhong, Xiaochen Wang, Jiaqi Wang +5
Synthesizing electronic health records (EHR) data has become a preferred strategy to address data scarcity, improve data quality, and model fairness in healthcare. However, existin…
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Liwei Che, Jiaqi Wang, Xinyue Liu +1
Federated learning (FL) has obtained tremendous progress in providing collaborative training solutions for distributed data silos with privacy guarantees. However, few existing wor…
CoRelation: Boosting Automatic ICD Coding Through Contextualized Code Relation Learning
Junyu Luo, Xiaochen Wang, Jiaqi Wang +3
Automatic International Classification of Diseases (ICD) coding plays a crucial role in the extraction of relevant information from clinical notes for proper recording and billing.…
Recent Advances in Predictive Modeling with Electronic Health Records
Jiaqi Wang, Junyu Luo, Muchao Ye +8
The development of electronic health records (EHR) systems has enabled the collection of a vast amount of digitized patient data. However, utilizing EHR data for predictive modelin…
Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
Suhan Cui, Jiaqi Wang, Yuan Zhong +3
The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improv…
MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation
Yuan Zhong, Suhan Cui, Jiaqi Wang +7
Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in…
Towards Personalized Federated Learning via Heterogeneous Model Reassembly
Jiaqi Wang, Xingyi Yang, Suhan Cui +4
This paper focuses on addressing the practical yet challenging problem of model heterogeneity in federated learning, where clients possess models with different network structures.…
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…
Active Learning for Product Type Ontology Enhancement in E-commerce
Yun Zhu, Sayyed M. Zahiri, Jiaqi Wang +2
Entity-based semantic search has been widely adopted in modern search engines to improve search accuracy by understanding users' intent. In e-commerce, an accurate and complete pro…