报告题目：k-Prototype Learning for 3D Rigid Structures
报告人：Jinhui Xu (徐金辉) 教授（State University of New York at Buffalo）
时间：2016年7月27日上午10:30-11:30
地点：天赐庄校区理工楼633室
报告摘要：In this paper, we study the following new variant of prototype learning, called k-prototype learning problem for 3D rigid structures: Given a set of 3D rigid structures, find a set of k rigid structures so that each of them is a prototype for a cluster of the given rigid structures and the total cost (or dissimilarity) is minimized. Prototype learning is a core problem in machine learning and has a wide range of applications in many areas. Existing results on this problem have mainly focused on the graph domain. In this paper, we present the first algorithm for learning multiple prototypes from 3D rigid structures. Our result is based on a number of new insights to rigid structures alignment, clustering, and prototype reconstruction, and is practically efficient with quality guarantee. We validate our approach using two type of data sets, random data and biological data of chromosome territories. Experiments suggest that our approach can effectively learn prototypes in both types of data.
报告人介绍：Dr. Xu is currently a professor of Computer Science and Engineering at the University at Buffalo (the State University of New York). He received his B.S. and M.S. degrees in Computer Science from the University of Science and Technology of China (USTC), and his Ph.D. degree in Computer Science and Engineering from the University of Notre Dame in 2000. Dr. Xu's research interest lies in the fields of Algorithms, Computational Geometry, Combinatorial Optimization, Machine Learning, and their applications in several applied areas. His recent research has focused on the development of geometric algorithms and machine learning methods for problems arising in medicine (medical imaging and interventional procedures for intracranial aneurysms), biology (determining the spatial patterns of chromosome organization inside the cell nucleus, as well as their alterations in cell differentiation, cell cycle, and progression of diseases such as cancer), networking, and 3D printing. Dr. Xu's research has been supported by National Science Foundation (NSF), National Institute of Health (NIH), NYSTAR, IBM, and University at Buffalo. He is a recipient of UB Exceptional Scholar: Sustained Achievement Award (2015), SEAS Senior Researcher of the Year Award (2015), the NSF CAREER Award (2005) and the IBM Faculty Partnership Award (2001).