2017 IEEE Symposium
on Computational Intelligence in Dynamic and Uncertain Environments
(IEEE CIDUE' 2017)
IEEE CIDUE' 2017 aims
to
bring together all researchers, practitioners
and students to present and discuss the latest advances in the field of
Computational Intelligence (CI), such as neural networks and learning
algorithms, fuzzy systems, evolutionary computation and other emerging
techniques for dealing with uncertainties encountered in evolutionary
optimization, machine learning and data mining.
Topics
- Evolutionary computation in dynamic and uncertain
environments
- Use of surrogates for single and multi-objective optimization
- Search for robust solutions over space and time
- Dynamic single and multi-objective optimization
- Handling noisy fitness functions
- Learning and adaptation in evolutionary computation
- Learning in non-stationary and uncertain environments
- Incremental and lifelong learning
- Online and interactive learning
- Dealing with catastrophic forgetting
- Active and autonomous learning in changing environments
- Ensemble techniques
- Multi-objective learning
- Learning from severely unbalanced data, including multiclass unbalanced data.
- Mining of temporal patterns
- Temporal data mining techniques and methodologies
- Incorporating domain knowledge for efficient temporal data mining
- Scalability of temporal data mining algorithms
- Mining of temporal data on the web
- Hybrid methodologies for dealing with uncertainties, interactions of evolution and learning in changing environments, benchmarks, performance measures, and real-world applications
Accepted
Special Sessions
(To be announced)
Organisers
 |
Shengxiang Yang De Montfort University, UK. Email:syang@dmu.ac.uk |
 |
Robi Polikar Rowan University, USA. Email: polikar@rowan.edu |
 |
Michalis Mavrovouniotis
Nottingham Trent University, UK. Email: michalis.mavrovouniotis@ntu.ac.uk |
 |
Yaochu Jin University of Surrey, UK. Email:yaochu.jin@surrey.ac.uk |
Program
Committee
- Marde Helbig, University of Pretoria, South Africa
- Yew-Soon Ong, Nanyang Technological University, Singapore
- Yongsheng Ding, Dong Hua University, China
- Xingguang Peng, Northwestern Polytechnical University, China
- Carlos Coello Coello, Cinvestav, Mexico
- Hongfeng Wang, Northeastern University, China
- Shih-Hsin Chen, Nanhua University Taiwan, Taiwan
- Haibin Duan, Beihang University, China
- Hamid Bouchachia, University of Klagenfurt, Austria
- Zexuan Zhu, Shenzhen University, China
- Zhun Fan, Shantou University, China
- Indre Zliobaite, Bournemouth University, UK
- Juergen Branke, University of Warwick, UK
- Ming Yang, China University of Geosciences, China
- Yang Yu, Nanjing University, China
- Jinliang Ding, Northeastern University, China
- Ivan Koyche,v University of Sofia, Bulgaria
- Defu Zhang, Xiamen University, China
- Swagatam Da,s Indian Statistical Institute, India
- Bin Li, University of Science and Technology of China, China
- Aimin Zhou, East China Normal University, China
- Chuan-Kang, Ting National Chung Cheng University, Taiwan
- David Pelta, University of Granada, Spain
- Chaoli Sun, University of Surrey, UK
- Siang-Yew, Chong University of Nottingham, Malaysia
- Chao Qian, Nanjing University, China