报告题目：Find global optimum for truth discovery entropy based geometric variance
报告人：Jinhui Xu (徐金辉) 教授（State University of New York at Buffalo）
时间：2016年7月7日上午9:30-10:30
地点：天赐庄校区理工楼633室
报告摘要：Truth Discovery is an important problem arising in data analytics related fields such as data mining, database, and big data. It concerns about finding the most trustworthy information from a dataset acquired from a number of unreliable sources. Due to its importance, the problem has been extensively studied in recent years and a number techniques have already been proposed. However, all of them are of heuristic nature and do not have any quality guarantee. In this paper, we formulate the problem as a high dimensional geometric optimization problem, called Entropy based Geometric Variance. Relying on a number of novel geometric techniques (such as Log-Partition and Modified Simplex Lemma), we further discover new insights to this problem. We show, for the first time, that the truth discovery problem can be solved with guaranteed quality of solution. Particularly, we show that it is possible to achieve a (1 +ε)-approximation within nearly linear time under some reasonable assumptions. We expect that our algorithm will be useful for other data related applications.
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).