43 citations · 95 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations
Yu Song, Jianxun Lian, Shuai Sun +4
User interest exploration is an important and challenging topic in recommender systems, which alleviates the closed-loop effects between recommendation models and user-item interac…
Local-Global Knowledge Distillation in Heterogeneous Federated Learning with Non-IID Data
Dezhong Yao, Wanning Pan, Yutong Dai +5
Federated learning enables multiple clients to collaboratively learn a global model by periodically aggregating the clients' models without transferring the local data. However, du…
Multi-Task Representation Learning with Multi-View Graph Convolutional Networks
Hong Huang, Yu Song, Yao Wu +3
Link prediction and node classification are two important downstream tasks of network representation learning. Existing methods have achieved acceptable results but they perform th…