5 citations · 5 across the 6 of their papers we have counts for
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cs.LG2023
GIMM: InfoMin-Max for Automated Graph Contrastive Learning
Xin Xiong, Furao Shen, Xiangyu Wang +1
Graph contrastive learning (GCL) shows great potential in unsupervised graph representation learning. Data augmentation plays a vital role in GCL, and its optimal choice heavily de…
cs.IR2023
Long-Term Value of Exploration: Measurements, Findings and Algorithms
Yi Su, Xiangyu Wang, Elaine Ya Le +12
Effective exploration is believed to positively influence the long-term user experience on recommendation platforms. Determining its exact benefits, however, has been challenging.…
cs.LG2023★ 5 cited
A Graph Neural Network with Negative Message Passing for Graph Coloring
Xiangyu Wang, Xueming Yan, Yaochu Jin
Graph neural networks have received increased attention over the past years due to their promising ability to handle graph-structured data, which can be found in many real-world pr…