Range searches in metric spaces can be very di cult if the space is \high dimensional", i.e. when the histogram of distances has a large mean and a small variance. The so-cal...
We describe a recursive algorithm to quickly compute the N nearest neighbors according to a similarity measure in a metric space. The algorithm exploits an intrinsic property of a...
stract to be announcedPlenary session 09:00-10:00 Panos M, Pardalos, University of Florida, USA Tea Break 10:00-10:20 At the 1st floor 10:20-10:45 Polynomial Approximation Schemes ...
We propose novel approaches for optimizing the detection performance in spoken language recognition. Two objective functions are designed to directly relate model parameters to tw...
We consider k-median clustering in finite metric spaces and k-means clustering in Euclidean spaces, in the setting where k is part of the input (not a constant). For the k-means pr...