New Challenges in Neural Computation (NC2)

Workshop of the GI-Arbeitskreis Neuronale Netze and the German Neural Networks Society in connection to DAGM 2011, Frankfurt

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Neural computation and biologically inspired data processing systems constitute essential topics in artificial intelligence accompanied by a well established theoretical foundation and numerous successful applications in science and industry. Although some of the most popular methods such as support vector machines or self-organizing maps are well established and readily available in commercial tools, modern information processing continues to pose challenging tasks to the field. Not only the amount of data explodes in virtually all application areas but also their complexity with regard to dimensionality, structural variety, and multimodality. At the same time, the tasks become more and more complex, moving from simple classification or prediction in pattern recognition to involved learning scenarios in dynamic environments with no explicit single objective. Humans are capable of handling complex situations and tasks by means of a combination of different paradigms, whereas existing neural systems mostly mirror only one or a few facets of the whole game.

This year, a special focus topic will center around the research area 'Autonomous learning and robotics'. In addition, general contribution to challenges in neural computation are welcome.

A non-exhaustive list of topics tackled in the workshop is given by the following keywords:


We welcome the submission of extended abstracts focussing on novel ideas and problems in the field. Submissions should be prepared as pdf files (e.g. using the latex article style) without page numbering, header, or footer, and should have one to four pages in length. Papers should be send to Barbara Hammer by e-mail ( until 30.7.2011.


Abstracts of the papers will be published online as Machine Learning Report.


For further questions, please contact the workshop organizers

ENNS The workshop is sponsored by the European Neural Networks Society
Barbara Hammer