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<div style="white-space:pre" align="center"> <a href="#C1"><b>Correspondence</b></a> <a href="#C2"><b>Biography</b></a> <a href="#C3"><b>Interests</b></a> <a href="#C4"><b>Resources</b></a> <a href="#C5"><b>Publications</b></a> </div>

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<!--Correspondence Part -->

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<h3><a name="C1">&nbsp; Correspondence</a></h3>

<li><b>Name:</b>

&nbsp; Yan-Ru Guo

<li><b>E-mail:</b>

&nbsp; <a href="mailto:">GuoYanRu211@163.com</a>

<li><b>Address:</b>

&nbsp; College of Science, Zhejiang University of Technology, Hangzhou, 310023, China

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<h3><a name="C2">&nbsp; Biography </a></h3></br>

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<b>Yan-Ru Guo</b> received her Bachelor's degree in College of Mathematics from Zhoukou normal University, China, in 2012. Currently, she is a third year graduate student of College of Science in Zhejiang University of Technology and a member of OPTIMAL Group, led by Yuan-Hai Shao. Her research interests include machine learning and data mining.

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<h3><a name="C3">&nbsp; Research Interests</a></h3>

<li><b class = "red">Machine learning and Data mining</b>

<p>&nbsp;&nbsp;&nbsp;&nbsp; Clustering

<p>&nbsp;&nbsp;&nbsp;&nbsp; Manifold learning

<p>&nbsp;&nbsp;&nbsp;&nbsp; Image processing

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<h3><a name="C5">Publications</a></h3>

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<li style="margin-right:5mm; margin-bottom:5mm;"> Wang C, Li C. N., Pei H. X., Guo Yan-Ru, Shao Y. H. Alternating direction method of multipliers for L1-and L2-norm best fitting hyperplane classifier. [J].</a> <b> Procedia Computer Science,</b>2017, 108: 1292-1301.EI

 

<li style="margin-right:5mm; margin-bottom:5mm;"> Liu L M,  Guo Yan- Ru, Wang Z, Yang Z M, Shao Y H*, k-Proximal plane clustering Alternating direction method of multipliers for L1-and L2-norm best fitting hyperplane classifier. [J].</a> <b> International Journal of Machine Learning and Cybernetics2016, 1~18SCI

 

<li style="margin-right:5mm; margin-bottom:5mm;"> Yang Zhi-Min, Guo Yan-Ru , Li Chun-Na , Shao Yuan-Hai. Local k-proximal plane clustering.</a> <b> Neural Computing and Applications</b>, 2015, 26(1): 199-211(SCI) <a href=" http://www.optimal-group.org/Resource/LkPPC.html">[Code].</a>

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