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We propose two solutions for both nearest neighbors and range search problems. For the nearest neighbors problem, we propose a c-approximate solution for the restricted version of the decision problem with bounded radius which is then reduced to the nearest neighbors by a known reduction. For range searching we propose a scheme that learns the parameters in a learning stage adopting them to the case of a set of points with low intrinsic dimension that are embedded in high dimensional spacedoi:10.1109/iccv.2013.431 dblp:conf/iccv/AigerKR13 fatcat:civavvlcevhbpcxczg3iwdgpsa