569 citations · 863 across the 13 of their papers we have counts for
4 papers · 1 filter
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding
Borui Cai, Yong Xiang, Longxiang Gao +4
Knowledge graph embedding (KGE) that maps entities and relations into vector representations is essential for downstream applications. Conventional KGE methods require high-dimensi…
An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation
Chenhao Xu, Youyang Qu, Tom H. Luan +3
Since the traffic conditions change over time, machine learning models that predict traffic flows must be updated continuously and efficiently in smart public transportation. Feder…
Prototype-Guided Memory Replay for Continual Learning
Stella Ho, Ming Liu, Lan Du +2
Continual learning (CL) refers to a machine learning paradigm that learns continuously without forgetting previously acquired knowledge. Thereby, major difficulty in CL is catastro…
SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems
Chenhao Xu, Jiaqi Ge, Yong Li +5
Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy. FL is effective when dealing with independent and identical…