Approximate range searching in higher dimension
نویسندگان
چکیده
Applying standard dimensionality reduction techniques, we show how to perform approximate range searching in higher dimension while avoiding the curse of dimensionality. Given points in a unit ball in , an approximate halfspace range query counts (or reports) the points in a query halfspace; the qualifier “approximate” indicates that points within distance of the boundary of the halfspace might be misclassified. Allowing errors near the boundary has a dramatic effect on the complexity of the problem. We give a solution with query time and !#" $
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