Abstract
Let X represent a sequence of data, and let XB represent an i.i.d. subsequence of length t of data generated from distribution B.1 Let F be a framework (in this case, a set of probability distributions or densities).2 Let MF be a method that takes a data sequence X as input and outputs a distribution B ∈ F; wewill typically drop the subscriptF from M as we will be dealing with a single framework at a time. Concretely, M[XB] = O means that M outputs O after observing the sequence XB . Let D be a distance metric over distributions (e.g., the Anderson-Darling test). Let Dδ(A, B) be shorthand for the following inequality: D(A, B) < δ. Finally, let [X,Y ] denote the concatenation of sequence X with sequence Y .
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