MIE Distinguished Seminar Series: Generative and Discriminative Learnings – A Fuzzy Restricted Boltzmann Machine and a Novel Broad Learning System

Date/Time
Date(s) - 29/09/2017
2:00pm-3:00pm


Speaker: Philip Chen, Dean and Chair Professor
Affiliation: University of Macau
Location: MC 102
Date and time: September 29, 2017, 2-3 PM

Abstract

In recent years, deep learning caves out a research wave in machine learning. With its outstanding performance, more and more applications of deep learning in pattern recognition, image recognition, speech recognition, and video processing have been developed. This talk will introduce a fuzzy generative deep learning algorithm and a novel broad learning systems. A fuzzy generative learning –  Fuzzy Restricted Boltzmann Machine (FRBM) – is developed by replacing real-valued weights and bias terms with symmetric triangular fuzzy numbers (STFNs) or Gaussian fuzzy numbers and corresponding learning algorithms. A theorem is concluded that all FRBMs with symmetric fuzzy numbers will have identical learning algorithm to that of FRBMs with STFNs.   The second part of the talk is to discuss a very fast and efficient discriminative learning – “Broad Learning”. Without stacking the layer-structure, the designed neural networks expand the neural nodes broadly and update the weights of the neural networks incrementally when additional nodes are needed and when the input data entering to the neural networks continuously. The designed network structure and learning algorithm are perfectly suitable for modeling and learning big data environment.  Experiments results in MNIST and handwriting recognition and NORB database indicate that the proposed BLS significantly outperforms existing deep structures in learning accuracy and generalization ability.

Speaker biosketch

Dr. Chen is currently the Dean of the Faculty of Science and Technology, University of Macau, Macau, China and a Chair Professor of the Department of Computer and Information Science since 2010. He worked at U.S. for 23 years as a tenured professor, a department head and associate dean in two different universities.

Dr. Chen’s research areas are in systems, cybernetics and computational intelligence. He is a Fellow of the IEEE and AAAS. He was the President of IEEE Systems, Man, and Cybernetics Society (SMCS) (2012-2013). Currently, he is the Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems (2014-). He has been an Associate Editor of many IEEE Transactions, and currently he is an Associate Editor of IEEE Trans on Fuzzy Systems, IEEE Trans on Cybernetics, and IEEE/CAA Automatica Sinica. He is the Chair of TC 9.1 Economic and Business Systems of IFAC. He is also a Fellow of CAA and Fellow of HKIE and an Academician of International Academy of Systems and Cybernetics Science (IASCYS). In addition, he is an ABET (Accreditation Board of Engineering and Technology Education, USA) Program Evaluator for Computer Engineering, Electrical Engineering, and Software Engineering programs.

 

Dr. Chen he received Outstanding Electrical and Computer Engineering Award in 2016 from his alma mater, Purdue University, West Lafayette, where he received his Ph.D. degree in 1988, after he received his M.S. degree in electrical engineering from the University of Michigan, Ann Arbor, in 1985.