Finding Best Solutions for Your Problems

--- A Mathematical Theory of Global Optimization

摘要：

The fundamental, unsolved problem in existing optimization methods is the lack of global optimality conditions. This lecture presents a new optimization method in a general form for solving this important problem. It does not struggle with local minima and offers us a complete departure from conventional optimization methods. This new theory has yielded the most powerful algorithms for LDPC decoding, stereovision, image reconstruction, constraint optimization, and other problems.

报告人简介:

Dr. Huang got his Ph.D. degree from Tsinghua University in 1990 under the guidance of Prof. Wu Youshou and Prof. Ding Xiaoqing. He developed the first multifont Chinese OCR system, which received several national awards. As a Post-Doc at University of Calgary, Canada, and visiting scientist at USC, USA, he proposed new approaches attacking hard combinatorial optimization problems, which greatly improved the best results at that time by several orders of magnitude. He then worked in several high tech companies in US as chief architect to design and developed distributed mobile computing platform and applications for enterprise computing (honored with several US patents). Starting from June 2005, he is the visiting Prof. of RIIT, Tsinghua University.

欢迎信息学院的广大师生参加!