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» Approximate Kernel Clustering
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TSP
2010
14 years 4 months ago
Quasi-interpolation by means of filter-banks
We consider the problem of approximating a regular function f(t) from its samples, f(nT), taken in a uniform grid. Quasi-interpolation schemes approximate f(t) with a dilated versi...
Gerardo Pérez-Villalón
SODA
2008
ACM
200views Algorithms» more  SODA 2008»
14 years 11 months ago
Clustering for metric and non-metric distance measures
We study a generalization of the k-median problem with respect to an arbitrary dissimilarity measure D. Given a finite set P, our goal is to find a set C of size k such that the s...
Marcel R. Ackermann, Johannes Blömer, Christi...
AAAI
2000
14 years 11 months ago
Multivariate Clustering by Dynamics
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
COLT
2003
Springer
15 years 3 months ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ļ¬...
Mehryar Mohri
PAMI
2007
253views more  PAMI 2007»
14 years 9 months ago
Gaussian Mean-Shift Is an EM Algorithm
The mean-shift algorithm, based on ideas proposed by Fukunaga and Hostetler (1975), is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density e...
Miguel Á. Carreira-Perpiñán