模式识别系列讲座

Lecture Series in Pattern Recognition

题    目 (TITLE)：Extreme Learning Machine: Towards Tuning-Free Learning

讲 座 人 (SPEAKER)：Dr. Guang-Bin Huang, School of Electrical and Electronic Engineering Nanyang Technological University, Singapore

主 持 人 (CHAIR)： Prof. Liang Wang

时    间 (TIME)：   July 25 (Thursday), 2013, 10:00AM

地    点 (VENUE)：No.3 Conference Room (3rd floor), Intelligence Building

报告摘要（ABSTRACT）：

Neural networks (NN) and support vector machines (SVM) play key roles in machine learning and data analysis in the past 2-3 decades. However, it is known that these popular learning techniques face some challenging issues such as: intensive human intervene, slow learning speed, poor learning scalability. This talk will introduce a next generation of learning theory; the resultant biologically inspired learning technique referred to as Extreme Learning Machine (ELM) and its wide applications. ELM not only learns up to tens of thousands faster than NN and SVMs, but also provides unified implementation for regression, binary and multi-class applications. ELM not only produces good results for sparse datasets but also is efficient for large size of applications. From both theoretical and practical points of view, NN and SVM/LS-SVM may only produce suboptimal solutions to ELM. Our preliminary study also shows that ELM outperforms Deep Learning in both learning accuracy and learning speed (up to tens of thousands times faster). ELM is efficient in time series, online sequential, incremental applications. More and more researchers are studying ELM and its potential applications in face recognition, EEG signal processing, brain computer interface, medical image processing, bioinformatics, disease prediction/detection, object recognition, knowledge discovery, data privacy, security, image quality assessment, semantic web, hardware implementation, cloud computing, and many other industrial applications.

报告人简介（BIOGRAPHY）：

Guang-Bin Huang received the B.Sc degree in applied mathematics and M.Eng degree in computer engineering from Northeastern University, P. R. China, in 1991 and 1994, respectively, and Ph.D degree in electrical engineering from Nanyang Technological University, Singapore in 1999. During undergraduate period, he also concurrently studied in Applied Mathematics department and Wireless Communication department of Northeastern University, P. R. China.He serves as an Associate Editor of Neurocomputing,neural networks, and IEEE Transactions on Systems, Man and Cybernetics - Part B. He is a senior member of IEEE. His SCI is 2300+ and HCI is 23.