Prof. Jon-Lark KimMath Department, Sogang University, Republic of Korea
Speech Title: Multi-class learning problems based on error-correcting output codes
Abstract: The multi-class classification problem is one of the important problems in machine learning. The common method to solve a multi-class classification problem is to decompose it into multiple binary problems. Dietterich and Bakiri in 1995 introduced the error-correcting output codes(ECOC) for this problem. The simplest decoding method, Hamming decoding, was employed to obtain a multi-class decision. In this presentation, we overview various ECOC methods and describe our recent work on ECOC based on Hadamard matrices.
Biography: Jon-Lark Kim received his Ph.D. in 2002 from Department of Math of the University of Illinois at Chicago. He was an Associate Professor at the University of Louisville until 2012. He is currently professor at Math Department of Sogang University in Seoul. He has authored more than fifty research papers and one book on Coding Theory. He is the recipient of the 2004 Kirkman medal from the Institute of Combinatorics and its Applications. His research interests include Coding Theory, Cryptography, Combinatorics, Bioinformatics, and Artificial Intelligence.