27 citations · 48 across the 5 of their papers we have counts for
5 papers
Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification
Xueliang Wang, Jianyu Cai, Shuiwang Ji +3
Few-shot classification aims to learn a model that can generalize well to new tasks when only a few labeled samples are available. To make use of unlabeled data that are more abund…
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings
Jie Wang, Zhanqiu Zhang, Zhihao Shi +3
Semantic matching models -- which assume that entities with similar semantics have similar embeddings -- have shown great power in knowledge graph embeddings (KGE). Many existing s…
Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021
Jianyu Cai, Jiajun Chen, Taoxing Pan +2
Link prediction in large-scale knowledge graphs has gained increasing attention recently. The OGB-LSC team presented OGB Large-Scale Challenge (OGB-LSC), a collection of three real…
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
Zhanqiu Zhang, Jianyu Cai, Jie Wang
Tensor factorization based models have shown great power in knowledge graph completion (KGC). However, their performance usually suffers from the overfitting problem seriously. Thi…
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang +1
Knowledge graph embedding, which aims to represent entities and relations as low dimensional vectors (or matrices, tensors, etc.), has been shown to be a powerful technique for pre…