Call for Papers WCCI 2016 Special Session on Linguistic Summarization and Description of Data

Organized by Nicolas Marin, Daniel Sanchez, Anna Wilbik, and Rui Jorge Almeida
http://decsai.ugr.es/pi/lidvis/cfpfuzzieee2016.html

Linguistic summaries and descriptions of data aim to extract and represent knowledge in the form of a collection of natural language sentences. The objective is to obtain a text, as if it was produced by a human expert, describing the most relevant aspects of data for a certain user in a specific context. Automatic generations of data summaries have gained increased relevance with the advent of possibilities to store and acquire data as well as relations between them. In this realm, not only specialized users (e.g. in decision support systems) are interested in this type of approach, but nonspecialized users also show interest in receiving understandable information that is supported by data.

Linguistic summaries commonly use fuzzy set theory to model linguistic variables and incorporate different forms of imprecision in a collection of natural language sentences. In many approaches they can be considered as quantifier based sentences, hence linguistic summaries constitute a perfect application for new developments in the domain of fuzzy quantifiers. Furthermore, linguistic summaries have been related to fuzzy rule systems. Linguistic summaries and description of data is related to other research areas such as knowledge discovery in databases and intelligent data analysis, flexible query answering systems for data, human-machine interaction, uncertainty management, heuristics and metaheuristics, natural language generation or processing. More recently, this field has been related to different paradigms, namely the linguistic description of complex phenomena and computing with words paradigms.

The objective of this special session is to provide a forum for researchers, from the above indicated areas, to present recent developments in linguistic summarizes and description of data as well as discuss how these different approaches can complement each other for the task of building such systems.

The session continues the series of special sessions on the topic organized by some of the organizers of this session in past conferences (IFSA 2015, FUZZ-IEEE 2015).

Topics of interest include, but are not restricted to:

• Protoforms and fuzzy concepts for the linguistic summaries and fuzzy description.
• Quality assessment of linguistic summaries and fuzzy description.
• Techniques and algorithms for generating linguistic summaries and descriptions of data.
• Ontologies for data summarization.
• Logical approaches for modeling linguistic expressions.
• Modeling uncertainty for linguistic summaries and fuzzy description.
• User preference/interest modeling for linguistic summaries and fuzzy description.
• Applications of linguistic summaries and fuzzy description.
• Natural language generation for data summarization.
• Machine Learning applied to data summarization.
• Linguistic information extraction from visual information
• Context-awareness in data summarization and description, and natural languageb generation.

Important dates:

Paper submission: January 15th, 2016
Notification of acceptance: March 15th, 2016
Final paper submission: April 15th, 2016
Early registration deadline: April 15th, 2016
Conference: July 25-29, 2016
Instructions for authors, submission and more details in the Conference website: http://www.wcci2016.org/

Accepted papers to this special session (if presented at the Conference) will be published in the conference proceedings of FUZZ-IEEE published by the IEEE.

Organizers:

Nicolas Marin. Department of Computer Science and Artificial Intelligence, University of Granada
e-mail: nicm@decsai.ugr.es

Daniel Sanchez. Department of Computer Science and Artificial Intelligence, University of Granada.
e-mail: daniel@decsai.ugr.es

Anna Wilbik. Information Systems, School of Industrial Engineering, Eindhoven University of Technology e-mail: a.m.wilbik@tue.nl

Rui Jorge Almeida. Information Systems, School of Industrial Engineering, Eindhoven University of Technology. e-mail: rjalmeida@tue.nl

Call for Papers WCCI 2016 Special Session: Computational intelligence techniques for the analysis of big and streaming data in complex systems

Aim:

Due to improved sensor technology, increasing storage space, and data availability, digital data sets are rapidly increasing with respect to size, dimensionality, and complexity. On the one hand, big and streaming data sets are becoming more and more popular in complex systems such as industrial manufacturing processes, surveillance, finance, social networks, or health-care. On the other hand, the dimensionality of data can easily reach a few thousand and data sources are often enriched by auxiliary information which gives crucial clues to avoid overfitting. These facts demand for advanced methods and tools which can cope with these big and complex data with respect to not only its sheer size, but also its often challenging statistical properties such as heterogeneous quality, data trends, presence of rare events, and necessity for strong regularisation. This special session will focus on advanced data analysis for big and streaming data which enable a reliable and computationally feasible access to such data sets.

Scope:

Submissions are encouraged according to the following non-exhaustive list of topics:

• Big data analytics
• Big data visualization
• Reliable machine learning for drift and trend
• Incremenental and lifelong learning
• Security and privacy in big data
• Regularization techniques for very high dimensional data
• Machine learning for heterogeneous and streaming data
• Constant memory algorithms for data analysis
• Analysis of sensor networks and social networks
• Distributed and multiple source machine learning techniques
• Big data applications e.g. in astronomy, health care, sensor networks
• Information and data fusion
• Semi-supervised learning
• Data correlation vs. information diversity

Submission by January 2016 at Congress website http://www.wcci2016.org/
 

Conference Proceedings:

This is a cross-disciplinary and CI applications Special Session, a submitted paper (if accepted and presented) will be published under one of the three conference proceedings (IEEE CEC, Fuzzy-IEEE, or IJCNN) that is most appropriate to the paper. Such decision will be made by the Special Session Organizers in consultation with the Special Session Chair and one of the three Conference Chairs.

Names of Organisers:

Prof.Barbara Hammer
CITEC centre of excellence
Bielefeld University
Germany
bhammer@techfak.uni-bielefeld.de

Prof.Frank Hsu
Department of Computer and Information Sciences
Fordham University, New York
USA
hsu@cis.fordham.edu

Prof.Marios M. Polycarpou
Department of Electrical and Computer Engineering
University of Cyprus, Nicosia
Cyprus

Call for Papers WCCI 2016 Special Session Computational Intelligence in Dynamics of Complex Networks: Models and Applications

Organized by Chung-Ming Ou and Chung-Ren Ou

Complex networks can be seen everywhere such as biology, chemistry, ecology, economics, physics, and even the Internet. There are many achievements in complex networks based on varied theories and models from mathematics and physics as well. However, the structures and internal properties of complex networks which lead to the major applications in sciences and technologies are still worth exploring. Among them, Computational Intelligence (CI) methodologies can be greatly contributed to solve these issues, in particular, the dynamics of complex networks. Applications of these CI methods to model and simulate complex networks are the main focus of this special session. The scope of the methodologies and ideas may include neural networks, artificial immune systems, swarm intelligence, fuzzy systems and other CI methods or general approaches from applied mathematics, physics, bio-inspired methodologies and control theory.

Scope and Topics

Topics of interest include but are not limited to:

• analysis and visualization of complex networks
• artificial immune systems
• big data and complex networks
• chaos in complex networks
• complex adaptive networks
• complex networks and self-organization
• control and dynamics of complex networks
• dynamics of complex networks
• mathematical modelling and analysis of complex networks
• modelling and simulation of biological networks
• robustness and stability of complex networks
• scale-free complex networks
• swarm intelligence and complex networks
• small-world complex network
• statistical properties of complex networks

Call for Papers WCCI 2016 Special Session: Spiking Neural Networks

Organisers: Nathan Scott & Nikola Kasabov (KEDRI, AUT)

Spiking Neural Networks are a rapidly emerging means of neural information processing, drawing inspiration from biological processes. There is presently considerable interest in this topic, especially with the recent announcement of large scale projects such as the “BRAIN Initiative” (US) and the “Human Brain Project” (EU). Due to their inspiration from human brain processes, SNN have the potential to advance technologies and techniques in fields as diverse as medicine, finance, computing, and indeed any field that involves complex spatio-temporal data. SNN can operate on noisy data, in changing environments at low power and with high effectiveness. We believe that this area is quickly establishing itself as an effective alternative to traditional machine learning technologies, and that interest in this area of research is growing rapidly. In this special session we intend to provide a platform for the discussion of contemporary areas of SNN, including theory, applications, and emerging technologies such as neuromorphic hardware.

Scope and Topics:

Topics of interest include, but are not limited to the following:

• Novel architectures
• SNN applications and case studies
• Learning algorithms for SNN, including Deep Learning 
• Big data and stream data processing in SNN
• Theory or practice in biologically realistic neural simulation or biomimetic models
•  Neuromorphic hardware systems and applications
• Robotic applications of SNN
• Theory of SNN
• Optimisation of SNN
• Evolving SNN
• Any other topics relating to Spiking Neural Networks, their theory, or application.

See http://www.wcci2016.org for conference and submission details.
The paper submission deadline is the 15th of January, 2016

WCCI 2016 Workshops

IEEE WCCI 2016 is pleased to confirm the following workshops:

1. Computational Energy Management in Smart Grids - organized by Stefano Squartini, Derong Liu, Francesco Piazza, Dongbin Zhao and Haibo He.
2. Neuromorphic Computing and Cyborg Intelligence - organized by Huajin Tang, Gang Pan, Arindam Basu and Luping Shi

Visit goo.gl/F0dAGA for more information about the workshops.

Call for Papers WCCI 2016 Special Session on Evolutionary Robotics

FIRST CALL FOR PAPERS

General Chairs:

Patricia A. Vargas (Heriot-Watt University - United Kingdom)
Joshua Auerbach (EPFL - Lausanne, Switzerland)
Micael Couceiro (Ingenarius, Ltd - Portugal)
Dario Floreano (EPFL - Lausanne, Switzerland)
Phil Husbands (University of Sussex - United Kingdom)


Website: http://lis2.epfl.ch/events/specialsessions/CEC16/

Evolutionary Robotics (ER) aims to apply evolutionary computation techniques, inspired by Darwin’s principle of selective reproduction of the fittest, to automatically design the control and/or hardware of both real and simulatedautonomous robots.

Having an intrinsic interdisciplinary character, ER is being employed towards the development of many fields of research, among which we can highlight neuroscience, cognitive science, evolutionary biology and robotics.

Hence the objective of this special session is to assemble a set of high-quality original contributions that reflect and advance the state-of-the-art in the area of Evolutionary Robotics, with an emphasis on the cross-fertilisation between ER and the aforementioned research areas, ranging from theoretical analysis to real-life applications.

Papers Publication:

Papers accepted to this special session track will be published in the IEEE CEC proceedings.

Post Conference Publication:

Authors of best papers will be asked to contribute to a journal special issue on the topic of "Evolutionary Robotics".

Paper Submission:

Submissions should follow the guidance given on the IEEE CEC 2016 conference website: http://www.wcci2016.org/submission.php

When submitting, please select in the submission system the respective special session title under the list of Main research topic: Evolutionary Robotics.

All submissions will be peer-reviewed with the same criteria used for  other contributed papers. All accepted papers will be included and published in the conference proceedings.

Topics of interest include (but are not restricted to):

• Evolution of robots which display minimal cognitive behaviour, learning, memory, spatial cognition, adaptation or homeostasis.
• Evolution of neural controllers for robots, aimed at giving an insight to neuroscientists, evolutionary biologists or advancing control structures.
• Evolution of communication, cooperation and competition, using robots as a research platform.
• Co-evolution and the evolution of collective behaviour.
• Evolution of morphology in close interaction with the environment, giving rise to self-reconfigurable, self-designing, self-healing, self-reproducing, humanoid and walking robots.
• Evolution of robot systems aimed at real-world applications as in aerial robotics, space exploration, industry, search and rescue, robot companions, entertainment and games.
• Evolution of controllers on board real robots or the real-time evolution of robot hardware.
• Novel or improved algorithms for the evolution of robot systems.
• The use of evolution for the artistic exploration of robot design.

Important Dates:

Paper Submission: January 15, 2016
Notification of Acceptance: March 15, 2016
Camera-Ready Submission: April 15, 2016

IEEE Transactions on Neural Networks and Learning Systems: Volume 26, Issue 11, November 2015

1. Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models
Authors: Feihu Huang; Songcan Chen
Page(s): 2606 - 2620

2. Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays
Authors: Huaguang Zhang; Junyi Wang; Zhanshan Wang; Hongjing Liang
Page(s): 2621 - 2634

3. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition
Authors: Yong Zhang; Peng Li; Yingyezhe Jin; Yoonsuck Choe
Page(s): 2635 - 2649

4. Noise Level Estimation for Model Selection in Kernel PCA Denoising
Authors: Carolina Varon; Carlos Alzate; Johan A. K. Suykens
Page(s): 2650 - 2663

5. Active Learning-Based Pedagogical Rule Extraction
Authors: Enric Junque de Fortuny; David Martens
Page(s): 2664 - 2677

6. Impulsive Multiconsensus of Second-Order Multiagent Networks Using Sampled Position Data
Authors: Zhi-Hong Guan; Guang-Song Han; Juan Li; Ding-Xin He; Gang Feng
Page(s): 2678 - 2688

7. Maximum Entropy Discrimination Poisson Regression for Software Reliability Modeling
Authors: Sotirios P. Chatzis; Andreas S. Andreou
Page(s): 2689 - 2701

8. Universal Memcomputing Machines
Authors: Fabio Lorenzo Traversa; Massimiliano Di Ventra
Page(s): 2702 - 2715

9. Incremental Linear Discriminant Analysis: A Fast Algorithm and Comparisons
Authors: Delin Chu; Li-Zhi Liao; Michael Kwok-Po Ng; Xiaoyan Wang
Page(s): 2716 - 2735

10. An Information-Based Learning Approach to Dual Control
Authors: Tansu Alpcan; Iman Shames
Page(s): 2736 - 2748

11. Decentralized Output Feedback Adaptive NN Tracking Control for Time-Delay Stochastic Nonlinear Systems With Prescribed Performance
Authors: Changchun Hua; Liuliu Zhang; Xinping Guan
Page(s): 2749 - 2759

12. Robust Nonnegative Patch Alignment for Dimensionality Reduction
Authors: Xinge You; Weihua Ou; Chun Lung Philip Chen; Qiang Li; Ziqi Zhu; Yuanyan Tang
Page(s): 2760 - 2774

13. Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer
Authors: Jialu Du; Xin Hu; Hongbo Liu; C. L. Philip Chen
Page(s): 2775 - 2786

14. An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction
Authors: Ronay Ak; Valeria Vitelli; Enrico Zio
Page(s): 2787 - 2800

15. MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis
Authors: Wanqi Yang; Yang Gao; Yinghuan Shi; Longbing Cao
Page(s): 2801 - 2815

16. On the Universality of Axon P Systems
Authors: Xingyi Zhang; Linqiang Pan; Andrei Paun
Page(s): 2816 - 2829

17. Recurrent Neural Network for Computing the Drazin Inverse
Authors: Predrag S. Stanimirovic; Ivan S. Zivkovic; Yimin Wei
Page(s): 2830 - 2843

18. Adaptive Neural Network Dynamic Surface Control for a Class of Time-Delay Nonlinear Systems With Hysteresis Inputs and Dynamic Uncertainties
Authors: Xiuyu Zhang; Chun-Yi Su; Yan Lin; Lianwei Ma; Jianguo Wang
Page(s): 2844 - 2860

19. Improved Learning Performance of Hardware Self-Organizing Map Using a Novel Neighborhood Function
Authors: Hiroomi Hikawa; Yutaka Maeda
Page(s): 2861 - 2873

20. Robust Multitask Multiview Tracking in Videos
Authors: Xue Mei; Zhibin Hong; Danil Prokhorov; Dacheng Tao
Page(s): 2874 - 2890

21. A Projection Neural Network for Constrained Quadratic Minimax Optimization
Authors: Qingshan Liu; Jun Wang
Page(s): 2891 - 2900

22. Multistability and Instability of Neural Networks With Discontinuous Nonmonotonic Piecewise Linear Activation Functions
Authors: Xiaobing Nie; Wei Xing Zheng
Page(s): 2901 - 2913

23. Finite-Time Stabilizability and Instabilizability of Delayed Memristive Neural Networks With Nonlinear Discontinuous Controller
Authors: Leimin Wang; Yi Shen
Page(s): 2914 - 2924

24. Model-Free Primitive-Based Iterative Learning Control Approach to Trajectory Tracking of MIMO Systems With Experimental Validation
Authors: Mircea-Bogdan Radac; Radu-Emil Precup; Emil M. Petriu
Page(s): 2925 - 2938

25. Enhanced Data-Driven Optimal Terminal ILC Using Current Iteration Control Knowledge
Authors: Ronghu Chi; Zhongsheng Hou; Shangtai Jin; Danwei Wang; Chiang-Ju Chien
Page(s): 2939 - 2948

26. Data-Driven H_\infty   Control for Nonlinear Distributed Parameter Systems
Authors: Biao Luo; Tingwen Huang; Huai-Ning Wu; Xiong Yang
Page(s): 2949 - 2961

27. Neurodynamics-Based Robust Pole Assignment for High-Order Descriptor Systems
Authors: Xinyi Le; Jun Wang
Page(s): 2962 - 2971

28. Sparse Density Estimation on the Multinomial Manifold
Authors: Xia Hong; Junbin Gao; Sheng Chen; Tanveer Zia
Page(s): 2972 - 2977

29. Spatiotemporal System Identification With Continuous Spatial Maps and Sparse Estimation
Authors: Parham Aram; Visakan Kadirkamanathan; Sean R. Anderson
Page(s): 2978 - 2983