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cs.LG2023
Cross-heterogeneity Graph Few-shot Learning
Pengfei Ding, Yan Wang, Guanfeng Liu
In recent years, heterogeneous graph few-shot learning has been proposed to address the label sparsity issue in heterogeneous graphs (HGs), which contain various types of nodes and…
cs.IR2023★ 1 cited
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
Feng Zhu, Mingjie Zhong, Xinxing Yang +8
In recommendation scenarios, there are two long-standing challenges, i.e., selection bias and data sparsity, which lead to a significant drop in prediction accuracy for both Click-…