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Special Sessions
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A. Computational Intelligence in Economics and Finance
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B. Neurodynamics
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C. Emotion and Artificial Intelligence Based E-Learning Networking and Education
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D. Extensions of Independent Component Analysis
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E. Business Applications of Neural Systems
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F. Advances in Machine Learning Methods based Pattern Recognition
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G. Incremental Self-Organizing Networks
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H. Cognitive Neuroscience in language Processing
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J. Intelligent Systems for Protein Analysis
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K. New Trends in Self-Organizing Maps
A. Computational Intelligence in Economics and Finance
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| Description: | Authors are invited to submit research and application papers representing original, previously unpublished work. Submissions are solicited in all areas of Computational Intelligence in Economics and Finance, including (but not limited to) the following: -Agent-Based Computational Economics -Simulation of Social Processes -Behavioral Finance -Experimental Economics -Simulation of Social Processes -Evolutionary Games -Artificial Stock Markets -Financial Data Mining -Financial Time Series Forecasting and Analysis -Financial Engineering -Trading Strategies -Portfolio Management -Hedging Strategies -Derivative Pricing -Term Structure Model | ||||
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B. Neurodynamics
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| Description: | The aim of this special session is to report the resent progresses in the field of dynamics of neural system. The emphasis will be on the modern approach to modeling the neuron and neural system, and to introduce the mathematical and physical techniques appropriate for analyzing the rich behavior of systems of interacting neurons. The researchers are mainly from theoretic fields such as mathematics, physics and mechanics, so it may be better for them having an exchanging and discussing opportunity, and they can understand the contents of the session fully. The subjects includes: -Models of the neuron -Networks of interacting phase oscillators -Traveling waves in neural systems -Firing rate models -Population models -Mean field descriptions for large networks, pattern formation in neural systems, etc. | ||
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C. Emotion and Artificial Intelligence Based E-Learning Networking and Education
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| Description: | In this session we wish to explore topics related to the theory and practical applications of various intelligence learning paradigms for e-learning and emotional system. Papers presenting new theoretical work are particularly sought. Philosophical papers discussing foundational issues are also suitable for inclusion. The list of topics includes but is not restricted to: -Simulation and Dynamic Equation of Intelligence Learning for Emotional Function and E-Learning -Relationship between Intelligence and Emotional System -Novel Intelligence Learning Structure for Emotional Function and E-Learning -Implementation Technology of Intelligent Learning for Emotional System and E-Learning -Network System based Technology (Control, Facility, Operation, Experiment) for Emotional System and E-learning System | ||
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D. Extensions of Independent Component Analysis
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| Description: | This special session focuses on the application-oriented extensions of independent component analysis (ICA) and their applications. The basic ICA model assumes that the underlying sources are mutually independent and that the data generation procedure is instantaneous and linear. Although it has some successful real-world applications, some extensions of ICA have been developed to relax the above assumptions and to allow ICA applicable to a wider range of data analysis area. These extensions include noisy ICA, independent subspace analysis, multidimensional ICA, (post-)nonlinear ICA, treedependent component analysis, and subband decomposition ICA, etc. Authors are invited to submit new findings on the theory and applications of ICA and its extensions. | ||
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E. Business Applications of Neural Systems
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| Description: | Neural networks have significant applications in Business and Economics. Several real-world applications are employing neural networks to solve practical problems that play a major role in everyday business functions, management and planning. As neural networks are being increasingly used for statistical modelling, they offer an alternative “intelligent” method of data processing that contributes added value to the business. As data analysis is a commonly used tool for strategic decision making, neural networks are being used for developing specialist tools such as those for predictive modelling, forecasting, market segmentation, classification of risks and optimization problems. This is a fast growing and promising field and many-a-times forms the basis of business intelligence. | ||
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F. Advances in Machine Learning Methods based Pattern Recognition
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| Description: | Many pattern recognition tasks, such as object recognition and retrieval, image segmentation, reconstruction, and document analysis, can be formulated and achieved from the viewpoint of machine learning. Machine learning based pattern recognition is becoming more and more popular as it provides a different way to reconsider some basic and important CVPR tasks. The purpose of this special session is to bring together the researchers with interests in this promising and quickly expanding field. Topics of interest include but not limited to: -Energy minimization based pattern recognition -Learning based objection detection -Other topics in machine learning based pattern recognition -Applications | ||||
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G. Incremental Self-Organising Networks
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| Description: | The aim of this special session is to report new developments, both in algorithms and application, of the incremental self-organising networks, which is a family of variants of the Kohonen’s Self-Organising Maps (SOM) belonging to the incremental self-organising networks. The well known examples are Dynamic Self-Organising Maps, Growing Self-Organising Maps, Growing Cell Structure, Growing Neural Gas, Incremental Grid Growing and Growing Grid. The known application areas of those networks include: -Bioinformatics -Mechatronics and Manufacturing -Hardware Implementations -Sensor Networks -Text analysis and mining -Information Visualization -Data mining and Knowledge Discovery -Coordination of Software Agents | ||||||
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H. Cognitive Neuroscience in language Processing
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| Description: | Recently, interdisciplinary research in language processing has been done. The cognitive neuroscientific approach on human may not only give us room to improve the performance of the natural language processing system but make understand the internal mechanism involved in human language processing. Topic of interest: -Human Language Processing -Computational Model of Human Language Processing -Neurolinguistics Computational Psycholinguistics -Neuroimaging Study on Human Language Processing | ||||
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J. Intelligent Systems for Protein Analysis
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| Description: | The dramatic growth of biological data has created an unprecedented opportunity for machine learning and pattern recognition community. Many biological problems involve pattern discovery and leaning. Increasingly, intelligent systems have been designed to solve problems in biology. This special session focuses specifically on intelligent systems for protein studies. The topic of interest includes (but not limits to) the following: -Protein structure prediction -Protein fold recognition -Protein function prediction -Motif discovery -Protein interaction prediction -Prediction of sub-cellular localization for proteins | ||||
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K. New Trends in Self-Organizing Maps
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| Description: | This special session deals with new trends in Self-Organizing Maps (SOM). Though SOM is one of the traditional neural network architectures, some new extensions and generalizations have been proposed recently, which enrich the SOM field drastically. Amongst, the fusion of modular network and SOM, i.e., the modular network SOM, has given a new aspect to the SOM field, because every nodal unit of the modular network SOM has an ability of information processing, whereas those of the conventional SOM are just static vectors. Therefore, the theories, extensions and applications of the modular network SOM would be the main topics of the special session. “SOM of SOMs” would be another main topic of the special session. It is also a type of modular network SOM, the modules of which are SOM themselves. It has also many applications. Some other new extensions of SOM are also welcome to this special session. | ||
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