100 citations · 249 across the 12 of their papers we have counts for
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cs.LG2023★ 1 cited
Generative Flow Networks for Precise Reward-Oriented Active Learning on Graphs
Yinchuan Li, Zhigang Li, Wenqian Li +3
Many score-based active learning methods have been successfully applied to graph-structured data, aiming to reduce the number of labels and achieve better performance of graph neur…
cs.LG2023★ 4 cited
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks
Wenqian Li, Yinchuan Li, Zhigang Li +2
Uncovering rationales behind predictions of graph neural networks (GNNs) has received increasing attention over the years. Existing literature mainly focus on selecting a subgraph,…
cs.LG2020
Optimizing AD Pruning of Sponsored Search with Reinforcement Learning
Yijiang Lian, Zhijie Chen, Xin Pei +10
Industrial sponsored search system (SSS) can be logically divided into three modules: keywords matching, ad retrieving, and ranking. During ad retrieving, the ad candidates grow ex…