2 citations · 3 across the 4 of their papers we have counts for
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cs.LG2023
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method
Shuo Han, Jiacheng Liu, Jiayun Wu +2
Graph Representation Learning (GRL) is an influential methodology, enabling a more profound understanding of graph-structured data and aiding graph clustering, a critical task acro…
cs.LG2023★ 2 cited
Predictive Heterogeneity: Measures and Applications
Jiashuo Liu, Jiayun Wu, Bo Li +1
As an intrinsic and fundamental property of big data, data heterogeneity exists in a variety of real-world applications, such as precision medicine, autonomous driving, financial a…
cs.LG2022★ 1 cited
Enhancing Distributional Stability among Sub-populations
Jiashuo Liu, Jiayun Wu, Jie Peng +4
Enhancing the stability of machine learning algorithms under distributional shifts is at the heart of the Out-of-Distribution (OOD) Generalization problem. Derived from causal lear…