168 citations · 486 across the 27 of their papers we have counts for
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cs.LG2022
Graph Augmentation Learning
Shuo Yu, Huafei Huang, Minh N. Dao +1
Graph Augmentation Learning (GAL) provides outstanding solutions for graph learning in handling incomplete data, noise data, etc. Numerous GAL methods have been proposed for graph-…
cs.LG2021★ 2 cited
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization
Canh T. Dinh, Tung T. Vu, Nguyen H. Tran +2
Non-Independent and Identically Distributed (non- IID) data distribution among clients is considered as the key factor that degrades the performance of federated learning (FL). Sev…