41 citations · 41 across the 2 of their papers we have counts for
2 papers
cs.IR2023
SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems
Beichuan Zhang, Chenggen Sun, Jianchao Tan +7
Increasing the size of embedding layers has shown to be effective in improving the performance of recommendation models, yet gradually causing their sizes to exceed terabytes in in…
cs.AI2021★ 41 cited
HMSG: Heterogeneous Graph Neural Network based on Metapath Subgraph Learning
Xinjun Cai, Jiaxing Shang, Fei Hao +2
Many real-world data can be represented as heterogeneous graphs with different types of nodes and connections. Heterogeneous graph neural network model aims to embed nodes or subgr…