On minimax rates of convergence in image models under sequential design
A binary image model is studied with a Lipschitz edge function. The indicator function of the image is observed in random noise at n design points that can be chosen sequentially. The asymptotically minimax rate as n-->[infinity] is found in estimating the edge function, and an asymptotically optimal algorithm is described.
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Volume (Year): 43 (1999)
Issue (Month): 4 (July)
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