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CIP 2008 : IAPR Workshop On Cognitive Information Processing

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Link: http://cip2008.di.uoa.gr/CIP08%20Papers.htm
 
When Jun 9, 2008 - Jun 10, 2008
Where Santorini (Thera), Greece
Abstract Registration Due Jan 5, 2008
Submission Deadline Mar 31, 2008
Categories    signal processing   machine learning   computer vision
 

Call For Papers

a bullet Overview

Over the recent years there is an increased need for Cognitive Information Processing (CIP) that extends the current systems engineering paradigm to one with the ability to perceive, learn, reason and interact robustly in open-ended changing environments. Real world problems and large digital environments (such as Internet) usually are too complex to be modelled within a limited set of predefined specifications. Thus, there will inevitably be a need for robust decisions and behaviour in novel situations based on the capability and knowledge of artificial cognitive systems. Further, there will be a need for automatic extraction and organization of meaning, purpose and intentions in interplay with the environment, beyond current systems, with built-in semantic representations and ontologies.

Research in CIP is widely interdisciplinary. The aim of this series of workshops is to bring together researchers from the Machine Learning, Pattern Recognition, Signal Processing and Communications communities, in an effort to encourage cross-fertilization of ideas and tools.

The event will take place in one of the world's most beautiful and impressive places, the Greek island of Santorini. The focus of the CIP 2008 workshop will be on Cognitive Radio.

CIP is sponsored by the International Association for Pattern Recognition (IAPR) and in particular the Signal Analysis for Machine Intelligence Technical Committee. The workshop will feature keynote addresses and technical presentations all of which will be included in the registration. Papers are solicited for, but not limited to, the following topics of interest.

a bullet Topics of Interest

Theory:
Learning theory and modelling
Bayesian learning and models
Information theoretic learning
Graphical and kernel methods
Adaptive learning algorithms
Ensembles: committees, mixtures, boosting, etc.
Data representation and analysis: PCA, ICA, CCA, etc.
Other related topics

Applications:
Cognitive radio
Cognitive component analysis
Cognitive dynamical systems
Distributed, cooperative and adaptive processing
Other related topics

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