Federated Continual Learning with Adaptive Parameter Communication

By Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang. 2020

17 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Jaehong Yoon
2. Sung Ju Hwang
3. Eunho Yang
4. Wonyoung Jeong
5. Giwoong Lee
6. Yansong Gao
7. Chandra Thapa
8. Minki Kim

Citations in the corpus

• Federated Continual Learning with Weighted Inter-client Transfer (2020, methodology): “for each client, and task-adaptive parameters for each specific task. This additive parameter decomposition scheme is motivated by a similar method for a single machine continual learning proposed by (Yoon et al., 2020). With this additive parameter decompositionscheme, a set of the model parameters ”
• End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things (2020, background): “There have been theoretical and empirical evaluations [13], [14] on the FL.”