Date: November 5, 2018
Time: 11:00 am
Location: Room E404, CSE Building
Admission: This event is free and open to all.
Metric Learning For Complex Data Analysis
Abstract: Comparing and measuring similarities or distances between pairs of instances is a basic but important step toward the success of many data mining and machine learning approaches. In this talk, I will discuss how both linear and nonlinear metric learning can be approached to capture various important relationships for complex data sets and how the learned metrics can be used for complex data analysis.
Biography: Aidong Zhang is a SUNY Distinguished Professor of Computer Science and Engineering at the State University of New York (SUNY) at Buffalo where she served as the Department Chair from 2009 to 2015. She is currently on leave and serving as a Program Director in the Information & Intelligent Systems Division of the Directorate for Computer & Information Science & Engineering, at the National Science Foundation. Her research interests include data mining/data science, machine learning, bioinformatics, and health informatics. Zhang currently serves as the Editor-in-Chief of the IEEE Transactions on Computational Biology and Bioinformatics (TCBB). Zhang is a fellow of ACM and IEEE.