Biography: Hirotaka Inoue received his B.E., M.E. and Ph.D. degrees from Okayama University of Science in 1997, 1999, and 2002, respectively. Currently he is an associate professor at Department of Electrical Engineering and Information Science, National Institute of Technology, Kure College. From 2006 to 2007, he was also a visiting researcher at University of Birmingham, UK. He received the IEEJ Best Paper Award in 2003 and 2007. His research interests include artificial intelligence, machine learning, and neural networks. He is a member of IEEE and IEICE.
Speech Title: Self-Organizing Neural Grove and Its Applications
Abstract: Recently, multiple classifier systems (MCS) have been used for practical applications to improve classification accuracy. Self-generating neural networks (SGNN) are one of the suitable base-classifiers for MCS because of their simple setting and fast learning. However, the computation cost of the MCS increases in proportion to the number of SGNN. In this talk, we will present a novel pruning method for efficient classification and we call this model as self-organizing neural grove (SONG). Experiments have been conducted to compare the pruned MCS with an unpruned MCS, the MCS based on C4.5, and k-nearest neighbor method. The results show that the pruned MCS can improve its classification accuracy as well as reducing the computation cost.