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科研进展

添加12字节, 2022年12月14日 (三) 22:38
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#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">[C]</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">.&nbsp;</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In&nbsp;'''''Proceedings of&nbsp;'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">&nbsp;'''''APWeb-WAIM 2022''''', Accepted</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NC-GNN: Consistent Neighbors of Nodes Help More in Graph Neural 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;">.'''''Wireless Communications and Mobile Computing''''', Accepted</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Lu H., Yang J., Fang W., Song X. and Wang C. A DNNs-based fusion model for COVID-19 rumor detection from online social media</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>&nbsp;<span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">'''''Data Technologies and Applications'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">, Accepted2022, 56(5): 806-824</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Cui F., Chen Y., Du Y., Cao Y. and Wang C. Joint Feature and Labeling Function Adaptation for Unsupervised Domain Adaptation</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">[C]</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">.</span></span>&nbsp;<span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In&nbsp;'''''Proceedings of &nbsp;PAKDD2022'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">, 432-446</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Zhang Y. Zhu Y., Zhang Z., Wang C.&nbsp;Collaboration based Multi-modal Multi-label Learning[J].&nbsp;'''Applied Intelligence'''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">,2022, 52(12): 14204-14217</span></span>
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