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= '''<span style="color:#800000"><span style="font-size:smaller">研究成果</span></span>''' =
#<span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">Liu Z., etc. FIXC: A Method for Data Distribution Shifts Calibration via Feature Importance[C]. </span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;"> </span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In '''''Proceedings of '''''<i>'''ICTAI 2022'''</i>, Accepted</span></span>
#<span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">Ge Y., etc. MRM: Site Selection via Mutil-round Meanshift for Global Fairness[C].</span></span> <span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;"> </span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In '''''Proceedings of ICTAI 2022''''', Accepted</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Yu H., etcYuan J., Yao Y., and Wang C. ''Not All Edges are Peers: Accurate Structure-Aware Graph Pooling Networks''</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">[J]</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">. '''''Neural Networks''''', 2022, 156: 58-66</span></span>
#<span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">Xu M., Zhang B., Cao M., Yu H., Wang C. LSEGNN: Encode Local Topology Structure in Graph Neural Networks[C].</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;"> </span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In '''''Proceedings of '''''<i>'''IPCCC 2022'''</i>, Accepted</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Zhang Y., Shen J., Yu C., Wang C. Views Meet Labels: Personalized Relation Refinement Network for Multiview Multilabel Learning</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">[J]</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">.</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">'''''IEEE Multim'''''. 2022, 29(2): 104-113</span></span>
