Prof. Jun Wang
Collective Neurodynamic Optimization Approaches to
Nonnegative Matrix Factorization
Prof. Jun Wang, Fellow IEEE and Fellow IARP
Chair Professor of Computational Intelligence
Department of Computer Science
City University of Hong Kong
Kowloon Tong, Kowloon, Hong Kong
Abstract: Nonnegative matrix factorization (NMF) is an advanced method for nonnegative feature extraction, with widespread applications. However, the NMF solution often entails to solve a global optimization problem with a nonconvex objective function and a nonnegativity constraint. To tackle this challenging problem, this paper presents a collective neurodynamic optimization approach by employing a population of recurrent neural networks (RNNs) at the lower level and particle swarm optimization (PSO) with wavelet mutation at the upper level. The RNNs act as search agents carrying out precise constrained local searches according to their neurodynamic equations and initial conditions. The PSO algorithm coordinates and guides the RNNs with updated initial states toward global optimal solution(s). A wavelet mutation operator is added in the optimization to enhance PSO exploration capability. Through iterative interaction and improvement of the locally best solutions of RNNs and global best positions of the whole population, the population-based neurodynamic systems is almost sure to achieve the global optimality for the NMF problem. The convergence of the group best state to the global optimal solution with probability one is proven. The experimental results substantiate the efficacy and superiority of the collective neurodynamic optimization approach to bound-constrained global optimization with several benchmark nonconvex functions and NMF-based clustering with benchmark datasets in comparison to the state-of-the-art algorithms.
Biography: Jun Wang is a Chair Professor Computational Intelligence in the Department of Computer Science at City University of Hong Kong. Prior to this position, he held various academic positions at Dalian University of Technology, Case Western Reserve University, University of North Dakota, and Chinese University of Hong Kong. He also held various short-term visiting positions at USAF Armstrong Laboratory, RIKEN Brain Science Institute, Huazhong University of Science and Technology, and Shanghai Jiao Tong University as a Changjiang Chair Professor, and Dalian University of Technology as a National Thousand-Talent Chair Professor. He received a B.S. degree in electrical engineering and an M.S. degree in systems engineering from Dalian University of Technology, Dalian, China. He received his Ph.D. degree in systems engineering from Case Western Reserve University, Cleveland, Ohio, USA. His current research interests include neural networks and their applications. He published over 170 journal papers, 15 book chapters, 11 edited books, and numerous conference papers in these areas. He is the Editor-in-Chief of the IEEE Transactions on Cybernetics since 2014 and a member of the editorial board of Neural Networks since 2012. He also served as an Associate Editor of the IEEE Transactions on Neural Networks (1999-2009), IEEE Transactions on Cybernetics and its predecessor (2003-2013), and IEEE Transactions on Systems, Man, and Cybernetics – Part C (2002–2005), as a member of the editorial advisory board of International Journal of Neural Systems (2006-2013), as a guest editor of special issues of European Journal of Operational Research (1996), International Journal of Neural Systems (2007), Neurocomputing (2008, 2014), and International Journal of Fuzzy Systems (2010, 2011). He was an organizer of several international conferences such as the General Chair of the 13th International Conference on Neural Information Processing (2006) and the 2008 IEEE World Congress on Computational Intelligence, and a Program Chair of the IEEE International Conference on Systems, Man, and Cybernetics (2012). He has been an IEEE Computational Intelligence Society Distinguished Lecturer (2010-2012, 2014-2016). In addition, he served as President of Asia Pacific Neural Network Assembly (APNNA) in 2006 and many organizations such as IEEE Fellow Committee (2011-2012); IEEE Computational Intelligence Society Awards Committee (2008, 2012, 2014), IEEE Systems, Man, and Cybernetics Society Board of Directors (2013-2015), He is an IEEE Fellow, IAPR Fellow, and a recipient of an IEEE Transactions on Neural Networks Outstanding Paper Award and APNNA Outstanding Achievement Award in 2011, Natural Science Awards from Shanghai Municipal Government (2009) and Ministry of Education of China (2011), and Neural Networks Pioneer Award from IEEE Computational Intelligence Society (2014), among others.