1 citations · 1 across the 7 of their papers we have counts for
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APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
Kejia Fan, Jianheng Tang, Zhirui Yang +8
Personalized Federated Learning (PFL) has presented a significant challenge to deliver personalized models to individual clients through collaborative training. Existing PFL method…
FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions
Jianheng Tang, Zhirui Yang, Jingchao Wang +7
Lately, Personalized Federated Learning (PFL) has emerged as a prevalent paradigm to deliver personalized models by collaboratively training while simultaneously adapting to each c…
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
Jianheng Tang, Huiping Zhuang, Jingyu He +10
Federated Continual Learning (FCL) enables distributed clients to collaboratively train a global model from online task streams in dynamic real-world scenarios. However, existing F…
RDPP-TD: Reputation and Data Privacy-Preserving based Truth Discovery Scheme in Mobile Crowdsensing
Lijian Wu, Weikun Xie, Wei Tan +3
Truth discovery (TD) plays an important role in Mobile Crowdsensing (MCS). However, existing TD methods, including privacy-preserving TD approaches, estimate the truth by weighting…
Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual Learning
Yajiang Huang, Jianheng Tang, Kejia Fan +6
In Continual Learning (CL), using a Pre-Trained Model (PTM) as the feature extractor has become a popular practice. Accompanied by analytic classifiers, the PTM-based methods have…