Deep learning has shown significantly promising performance in addressing real-world problems, such as image recognition, natural language processing and self-driving. The achievements of such algorithms owe to its deep structures. However, designing an optimal deep structure for a particular problem requires rich domain knowledge on both the investigated data and the general data analysis domain, which is not necessarily held by the end-users. In addition, the problem of searching for the optimal structure could be non-convex and non-differentiable, and existing accurate methods are incapable of well addressing it. Furthermore, the deep structure defined for the task is not reusable, i.e., a new one must be redesigned for data with a slightly changed scenario and/or unseen data.
Evolutionary computation (EC) approaches, particularly genetic algorithms (GAs), particle swarm optimization (PSO) and genetic programming (GP), have shown superiority in addressing real-world problems due largely to their powerful abilities in searching for global optima, dealing with non-convex/non-differentiable problems, and requiring no rich domain knowledge. However, most of the existing EC methods currently work only on relatively shallow structures, and cannot provide satisfactory results in searching for deep structures. In this regard, deep learning structures designed by EC approaches, i.e., evolutionary deep learning, would be a great research topic.
The theme of this special session aims to bring together researchers investigating methods and applications in evolutionary deep learning. Particularly, the methods focus on effective and efficient representations, search mechanisms and optimization techniques. Authors are invited to submit their original and unpublished work to this special session.
Please follow the IEEE CEC2019 Submission Web Site. Special session papers are treated the same as regular conference papers. Please specify that your paper is submitted to special session "Evolutionary Deep Learning and Applications". All papers accepted and presented at CEC2019 will be included in the conference proceedings published by IEEE Explore, which are typically indexed by EI.
Yanan Sun received his PhD degree from Sichuan University in Chengdu, China in 2017. He has been a jointly PhD student from August 2015 to February 2017 in Oklahoma State University, USA. He is currently a research fellow with the School of Engineering and Computer Science, Victoria University of Wellington, New Zealand. His areas of expertise include deep learning, many-objective optimization and evolutionary deep learning. He has co-supervised one summer student and is co-supervising an Honours student. Dr Sun has published 10 papers on deep neural networks and evolutionary algorithms in fully-refereed international journals and conferences including four papers in top journals IEEE Transactions on Evolutionary Computation and Knowledge-based System, and he also has submitted four papers to IEEE Transactions on Evolutionary Computation, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Pattern Analysis and Machine Intelligence for review. Although being emergent, he has been a reviewer of >10 international journals/conferences and program committee member for international conferences. Further, the paper “Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations”, where Dr sun is the first author, is the first one published by IEEE Transactions on Evolutionary Computation on the topic of evolutionary deep learning. He is co-organizer of the first workshop on “Evolutionary Deep Learning” and the founding chair of IEEE CIS Task Force on “Evolutionary Deep Learning and Applications”
Bing Xue is currently a Senior Lecturer in School of Engineering and Computer Science at Victoria University of Wellington. Her research focuses mainly on evolutionary computation, feature selection, feature construction, multi-objective optimisation, data mining and machine learning. She has over 100 papers published in fully referred international journals and conferences. She is currently co-supervising over 10 PhD students and visiting scholars, and over 10 Honours and summer research projects. Dr Xue is currently the Chair of the IEEE CIS Task Force on Evolutionary Feature Selection and Construction, and an Associate Editor/member of Editorial Board for five international journals including IEEE Computational Intelligence Magazine, Applied Soft Computing, International Journal of Swarm Intelligence, and International Journal of Computer Information Systems and Industrial Management Applications. She is a Guest Editor for the Special Issue on Evolutionary Feature Reduction and Machine Learning for the Springer Journal of Soft Computing. She is also a Guest Editor for Evolutionary Image Analysis and Pattern Recognition in Journal of Applied Soft Computing. She is serving as a reviewer of over 20 international journals including IEEE Transactions on Cybernetics and IEEE Transactions on Evolutionary Computation. She has been a chair for a number of international conferences including the Leading Chair of IEEE Symposium on Computational Intelligence in Feature Analysis, Selection, and Learning in Image and Pattern Recognition at SSCI 2016 and 2017, a Program Co-Chair of the 31th Australasian AI 2018, ACALCI 2018, and the 7th International Conference on SoCPaR2015, Special Session Chair for The 20th Asia-Pacific Symposium on Intelligent and Evolutionary Systems (IES2016), a Tutorial Chair for the 30th Australasian AI, publicity chair for the international conference on Simulated Evolution And Learning (SEAL) 2017, and International Conference on Data, Intelligence and Security (ICDIS) 2018. She is the organiser of the special session on Evolutionary Feature Selection and Construction in IEEE Congress on Evolutionary Computation (CEC) 2015, 2016 and 2017, and SEAL 2014 and 2017. Dr Xue is chairing the IEEE CIS Graduate Student Research Grants Committee and the Secretary of the IEEE Chapter on Computational Intelligence in that Section.
Chuan-Kang Ting received the B.S. degree from National Chiao Tung University, Taiwan, in 1994, the M.S. degree from National Tsing Hua University, Taiwan, in 1996, and the Ph.D. degree from the University of Paderborn, Germany, in 2005. He is currently a Professor at Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan. His research interests are in evolutionary computation, computational intelligence, metaheuristic algorithms, and their applications in transportation and logistics networks, bioinformatics, music and games. He is an Associate Editor of IEEE Computational Intelligence Magazine and IEEE Transactions on Emerging Topics in Computational Intelligence, and an Editorial Board Member of Soft Computing and Memetic Computing journals. He chaired the AI Forum 2012 and co-chaired the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing.
Mengjie Zhang is currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation Research Group. He is a member of the University Academic Board, a member of the University Postgraduate Scholarships Committee, a member of the Faculty of Graduate Research Board at the University, Associate Dean (Research and Innovation) in the Faculty of Engineering, and Chair of the Research Committee of the Faculty of Engineering and School of Engineering and Computer Science. His research is mainly focused on evolutionary computation, particularly genetic programming, particle swarm optimisation and learning classifier systems with application areas of feature selection/construction and dimensionality reduction, computer vision and image processing, job shop scheduling, multi-objective optimisation, and classification with unbalanced and missing data. He is also interested in data mining, machine learning, and web information extraction. Prof Zhang has published over 400 research papers in refereed international journals and conferences in these areas. He has been serving as an associated editor or editorial board member for seven international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press), Genetic Programming and Evolvable Machines (Springer), Applied Soft Computing, IEEE Transactions on Emergent Topics in Computational Intelligence, Natural Computing, and Engineering Applications of Artificial Intelligence, and as a reviewer of over 30 international journals. He has been involving major EC conferences such as GECCO, IEEE CEC, EvoStar, IEEE SSCI and SEAL as a Chair. He has also been serving as a steering committee member and a program committee member for over 100 international conferences including all major conferences in evolutionary computation. Since 2007, he has been listed as one of the top ten world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html). Prof. Zhang is the Chair of the IEEE CIS Intelligent Systems and Applications Technical Committee (ISATC), a member of the IEEE CIS Evolutionary Computation Technical Committee, a Vice-Chair of the IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing, a Vice-Chair of the IEEE CIS Task Force on Evolutionary Computation for Feature Selection and Construction, a member of IEEE CIS Task Force of Hyper-heuristics, and the Founding Chair for IEEE Computational Intelligence Chapter in New Zealand.