Special Session on Sequential Learning with Neural Networks
Image header of WCCI 2016

The 2016 IEEE World Congress
on Computational Intelligence (IEEE WCCI 2016)

Special Session on

Sequential Learning with Neural Networks

Huanhuan Chen1, Giacomo Boracchi2, and Jian Cheng3

Introduction to the special session

Over the past few decades, research and applications of sequential data has attracted growing attention from both scientific and industrial communities. A number of processing techniques have been proposed for sequential data understanding and processing, e.g. dynamic time warping (DTW), fisher kernel and recurrent neural networks. The main aim of this special session is not only to explore the new techniques on this area, providing original research with the aim for deeper understanding into the mechanism of algorithms, but also to encourage exchange of great ideas on sequential learning in different scenarios. We wish to communicate with people working in different research areas, practitioners, professionals and academicians in this area.

Topics of the special session include, but not limited to:

  • recurrent neural networks
  • Sequential data classification, regression and learning
  • Architectures, techniques and algorithms for learning in non-stationary/dynamic environments
  • Domain adaptation, dataset shift, covariance shift
  • Incremental learning, lifelong learning, cumulative learning
  • Change-detection tests and anomaly-detection algorithms
  • Mining from streams of data
  • Sequential kernel
  • Text Classification
  • streaming learning and mining
  • hidden Markov models
  • Echo state networks, and reservoir models
  • Applications that call for incremental learning or learning in non-stationary/dynamic environments, such as:
  • Cognitive-inspired approaches to adaptation and learning
  • Finite state machines and Dynamic models
  • Issues relevant to above mentioned or related fields
  • Organizers

    Huanhuan Chen is a professor in School of Computer Science, University of Science & Technology of China (USTC), Hefei, China. He received the B.Sc. degree from USTC, Hefei, China, in 2004, and Ph.D. degree, sponsored by Dorothy Hodgkin Postgraduate Award, in computer science at the University of Birmingham, Birmingham, UK, in 2008. He worked in University of Birmingham and University of Leeds in the UK from 2008 to 2012, respectively. From 2012, he has been selected to young thousand talent program by central government and became a professor in USTC. He has received 2011 IEEE Computational Intelligence Society Outstanding PhD Dissertation award (the only winner), 2009 CPHC/British Computer Society Distinguished Dissertations Award (the runner up), IEEE Transactions on Neural Networks Outstanding 2009 Paper Award (bestowed in 2012, and only one paper in 2009 receive this award), and 2015 the International Neural Network Society (INNS) Young Investigator Award.

    Giacomo Boracchi graduated in Mathematics at Universita Statale degli Studi di Milano, Italy, in 2004 and in 2005. He has been researcher at Tampere International Center for Signal Processing, Finland. In 2008 he received a Ph.D. in Information Technology at the Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy. Currently, he is an assistant professor at Dipartimento di Elettronica e Informazione, Politecnico di Milano, and he is actively collaborating with Computational Imaging group in the Department of Signal Processing, Tampere University of Technology. His research interests encompass two different areas: computational intelligence and image analysis and enhancement. In particular, his research activity covers the following lines: learning methods for nonstationary environments, change/anomaly detection, computational imaging, and image restoration. He received 2015 IBM Faculty Award and the 2016 IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Award.

    Jian Cheng is currently an associate professor with China University of Mining and Technology, Xuzhou, China. He received the B. Eng. degree in Industrial Automation, the M. Sc. Degree in Control theory and Control Engineering, and the Ph. D. degree in Communication and Information System from China University of Mining and Technology, in 1997, 2003 and 2008, respectively. He worked at Tsinghua University as a postdoctoral researcher from Jun. 2009 to Aug. 2011. During Jan. 2012 to Jan. 2013, he visited University of Birmingham as a postdoctoral fellow supported by China Scholarship Council. His research interests are broadly in the area of Machine Learning, Intelligent Computing, Fault Detection and Diagnosis, Monitoring and Control System. He has published over 30 papers in journals and conferences, and holds a granted software patent.


    1School of Computer Science, University of Science & Technology of China, Hefei, Anhui, 230026.

    2Dipartimento di Elettronica e Informazione, Politecnico di Milano.

    3School of Information and Electrical Engineering, China University of Mining and Technology.