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IJCAI
2003
14 years 11 months ago
Distributed Clustering Based on Sampling Local Density Estimates
Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
Matthias Klusch, Stefano Lodi, Gianluca Moro
PRL
2006
153views more  PRL 2006»
14 years 9 months ago
Efficient adaptive density estimation per image pixel for the task of background subtraction
We analyze the computer vision task of pixel-level background subtraction. We present recursive equations that are used to constantly update the parameters of a Gaussian mixture m...
Zoran Zivkovic, Ferdinand van der Heijden
CDC
2008
IEEE
126views Control Systems» more  CDC 2008»
14 years 11 months ago
Subspace identification using predictor estimation via Gaussian regression
In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...
JMLR
2010
118views more  JMLR 2010»
14 years 4 months ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
92
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ICASSP
2011
IEEE
14 years 1 months ago
Robust nonparametric regression by controlling sparsity
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
Gonzalo Mateos, Georgios B. Giannakis