NC² New Challenges in Neural Computation (NC2)
Workshop of the GI-Fachgruppe Neuronale Netze and the German Neural Networks Society in connection to GCPR 2014, Münster

Call for Papers

Neural computation and machine learning have revolutionized automatic data processing, opening the ground towards problems which cannot be modeled with classical statistical techniques. Interestingly, besides techniques which have its roots in mathematical frameworks such as the support vector machine, quite a few methods have been inspired by cognitive models such as deep networks, or reservoir computing. Still, there exist quite a few challenges in this domain: 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.

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

ENNS The workshop is sponsored by the European Neural Networks Society and by the CITEC centre of excellence CITEC: Cognitive Interaction Technology - Center of Excellence

Barbara Hammer