计算机理论与软件研究所诚挚邀请到美国纽约州立大学（布法罗）徐金辉教授来中南大学客座讲学。徐金辉教授将做主题为“On Truth Discovery and Its Applications”的学术报告。
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 talk, 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, Modified Simplex Lemma, and Range Cover), 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 + epsilon)-approximation within nearly quadratic time. We expect that our algorithm will be useful for other data related applications.
Dr. Jinhui Xu received his BS and MS degrees in Computer Science from the University of Science and Technology of China in 1992 and 1995 respectively and his PhD degree in Computer Science and Engineering from the University of Notre Dame (Indiana, USA) in 2000. Since then, he is on the faculty of Computer Science and Engineering at the State University of New York at Buffalo (UB), and is currently a full professor and associate chair. His research interest lies in the areas of algorithms, computational geometry, optimization, machine learning and their applications in medicine, biology, big data, networking, and 3D printing. He has published over 180 research papers in these areas （many of them appeared in the prestigious international conferences and journals），designed the state-of-the-art algorithms for many fundamental problems （including several longstanding open problems）， generalized a class of geometric structures and classical problems, and obtained a number of general tools for algorithm designs. He is one of the pioneers who use geometric techniques to solve challenging biomedical problems. His research on determining the spatial organization and dynamics of the cell nucleus has led to several internationally acclaimed biological discoveries and been awarded cover pages by several major biological journals. He is a recipient of several prestigious awards, including the NSF CAREER Award, UB Exceptional Scholar: Sustained Achievement Award, and SUNY Chancellor’s Award for Excellence in Scholarship and Creative Activities.