13 citations · 20 across the 4 of their papers we have counts for
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cs.LG2024★ 1 cited
Variational Bayes for Federated Continual Learning
Dezhong Yao, Sanmu Li, Yutong Dai +4
Federated continual learning (FCL) has received increasing attention due to its potential in handling real-world streaming data, characterized by evolving data distributions and va…
cs.LG2024★ 5 cited
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
Jun Yu, Yutong Dai, Xiaokang Liu +14
MTL is a learning paradigm that effectively leverages both task-specific and shared information to address multiple related tasks simultaneously. In contrast to STL, MTL offers a s…
cs.LG2021★ 13 cited
FedHM: Efficient Federated Learning for Heterogeneous Models via Low-rank Factorization
Dezhong Yao, Wanning Pan, Michael J O'Neill +4
One underlying assumption of recent federated learning (FL) paradigms is that all local models usually share the same network architecture and size, which becomes impractical for d…