Dr. Jin-Kao Hao holds the title of Distinguished Professor at the Computer Science Department of the University of Angers (France) and is senior fellow of the Institut Universitaire de France. He headed the LERIA Lab. from 2003 until 2015. His research lies in the design of effective algorithms and intelligent computational methods for solving large-scale combinatorial search problems. He is interested in various application areas including bioinformatics, data science, telecommunication, complex networks, and transportation. He has published some 220 papers including 110 SCI journal papers and co-edited 9 books in Springer’s LNCS series. He has served on some 200 Program Committees of International Conferences and is on the Editorial Board of 7 International Journals.
报告摘要：In this talk we present some case studies of using learning and data mining techniques for solving combinatorial optimization: multidimensional scaling and reinforcement learning for graph coloring, opposition-based learning for subset selection with maximum diversity, and frequent patterns for quadratic assignment. We show how learning and data mining techniques techniques can be advantageously combined with an optimization method to obtain high-quality results for difficult combinatorial optimization problems.