activity
20182024
most citedDecentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend

17 citations · 30 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2024★ 11 cited

FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction

Muhao Xu, Zhenfeng Zhu, Youru Li +4

Multimodal electronic health record (EHR) data can offer a holistic assessment of a patient's health status, supporting various predictive healthcare tasks. Recently, several studi…

cs.LG2023

Markov Chain Mirror Descent On Data Federation

Yawei Zhao

Stochastic optimization methods such as mirror descent have wide applications due to low computational cost. Those methods have been well studied under assumption of the independen…

cs.AI2023★ 2 cited

Medical Federated Model with Mixture of Personalized and Sharing Components

Yawei Zhao, Qinghe Liu, Xinwang Liu +1

Although data-driven methods usually have noticeable performance on disease diagnosis and treatment, they are suspected of leakage of privacy due to collecting data for model train…

cs.LG2019

Simultaneous Clustering and Optimization for Evolving Datasets

Yawei Zhao, En Zhu, Xinwang Liu +3

Simultaneous clustering and optimization (SCO) has recently drawn much attention due to its wide range of practical applications. Many methods have been previously proposed to solv…

cs.LG2019★ 17 cited

Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend

Yawei Zhao, Chen Yu, Peilin Zhao +3

Decentralized Online Learning (online learning in decentralized networks) attracts more and more attention, since it is believed that Decentralized Online Learning can help the dat…

cs.LG2018

Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets

Yawei Zhao, Kai Xu, Xinwang Liu +3

Recently, network lasso has drawn many attentions due to its remarkable performance on simultaneous clustering and optimization. However, it usually suffers from the imperfect data…