106 citations · 246 across the 20 of their papers we have counts for
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cs.LG2021★ 4 cited
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu
An effective approach in meta-learning is to utilize multiple "train tasks" to learn a good initialization for model parameters that can help solve unseen "test tasks" with very fe…
cs.LG2020★ 1 cited
Rule-Guided Graph Neural Networks for Recommender Systems
Xinze Lyu, Guangyao Li, Jiacheng Huang +1
To alleviate the cold start problem caused by collaborative filtering in recommender systems, knowledge graphs (KGs) are increasingly employed by many methods as auxiliary resource…
cs.LG2018
DSKG: A Deep Sequential Model for Knowledge Graph Completion
Lingbing Guo, Qingheng Zhang, Weiyi Ge +2
Knowledge graph (KG) completion aims to fill the missing facts in a KG, where a fact is represented as a triple in the form of . Current KG completion…