Search Results for author: Chengjun Lu

Found 2 papers, 0 papers with code

FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning

no code implementations23 Jun 2023 Rishub Tamirisa, John Won, Chengjun Lu, Ron Arel, Andy Zhou

Recent advancements in federated learning (FL) seek to increase client-level performance by fine-tuning client parameters on local data or personalizing architectures for the local task.

Personalized Federated Learning

Deep Contrastive Graph Representation via Adaptive Homotopy Learning

no code implementations17 Jun 2021 Rui Zhang, Chengjun Lu, Ziheng Jiao, Xuelong Li

In particular, in this paper, we apply AH to contrastive learning (AHCL) such that it can be effectively transferred from weak-supervised learning (given label priori) to unsupervised learning, where soft labels of contrastive learning are directly and adaptively learned.

Contrastive Learning

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