Learning dynamical systems in a stationary environment
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abstract
The recently emerging field of learning theory, pioneered by Vapnik and Chervonenkis, has by and large been focused on the problem of learning static relations. As an initial attempt to extend this approach to system identification, we examine the problem of learning input-output relations in a stationary environment.
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Proceedings of 35th IEEE Conference on Decision and Control