Approximate Learning of Dynamic Models/Systems
Dynamical systems model the evolution of a system with unknown parameters. The goal of a learning procedure is to estimate the parameters of the system, possibly from a set of known examples, such that the system behavior on future inputs is accurately predicted. Such a learning procedure typically uses methodologies from techniques in statistics and computer science and can be computationally intractable for some systems.
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