报告题目：Towards distributed ensemble clustering for networked sensing systems: a novel geometric approach
报告人：Jinhui Xu (徐金辉) 教授（State University of New York at Buffalo）
时间：2016年7月11日上午 10:30-11:30
地点：天赐庄校区理工楼633室
报告摘要：Given a set of different clustering solutions to a unified dataset, ensemble clustering is to aggregate them to yield a more accurate and robust solution. In recent years, ensemble clustering has been extensively studied and successfully applied to many areas. In this paper, we study a new variant of ensemble clustering, distributed ensemble clustering, motivated by the proliferation of networked sensing systems where communication is enabled between only connected nodes. Our goal is to aggregate the clustering solutions produced by the sensor nodes that observe the same set of objects. Different from traditional ensemble clustering problems, distributed ensemble clustering aims to achieve not only accurate clustering results, but also low communication cost among the nodes. To this end, we build a novel geometric optimization model that can be efficiently solved with theoretical quality guarantee. The proposed approach, bearing nice geometric properties, can be easily adapted to distributed settings without any sacrifice of clustering quality, and facilitates a dimension reduction procedure which can significantly reduce the communication complexity. We validate our approach on two benchmark datasets. Experimental results suggest that our approach can efficiently solve the distributed ensemble clustering problem, and outperform the baselines on both clustering accuracy and communication cost.
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).