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--- seminars:datasci:210504 [2021/04/23 12:39] – created qyu
+++ seminars:datasci:210504 [2021/04/23 12:40] (current) – qyu
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+<WRAP centeralign>##Data Science Seminar##\\ Hosted by Department of Mathematical Sciences</WRAP>
+  * Date: Tuesday, May 4, 2021
+  * Time: 12:00pm -- 1:00pm
+  * Room: Zoom meeting
+  * Speaker: Zhou Wang (Binghamton University)
+  * Title: Multiclass Anomaly Detector: the CS++Support Vector Machine
+<WRAP center box 80%>
+<WRAP centeralign>**//Abstract//**</WRAP>
+A new support vector machine (SVM) variant, called CS++SVM, is presented
+combining multiclass classification and anomaly detection in a single-step process to
+create a trained machine that can simultaneously classify test data belonging to
+classes
+represented in the training set and label as anomalous test data belonging to
+classes not
+represented in the training set. A theoretical analysis of the properties of the new
+method, showing how it combines properties inherited both from the
+conic-segmentation SVM
+(CS-SVM) and the 1-class SVM. Finally, experimental results are presented to
+demonstrate
+the effectiveness of the algorithm for both simulated and real-world data.
+</WRAP>