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» Density Estimation: Nonparametric Techniques
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JMLR
2011
133views more  JMLR 2011»
13 years 18 days ago
Operator Norm Convergence of Spectral Clustering on Level Sets
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
Bruno Pelletier, Pierre Pudlo
ICANN
2007
Springer
13 years 7 months ago
GARCH Processes with Non-parametric Innovations for Market Risk Estimation
Abstract. A procedure to estimate the parameters of GARCH processes with non-parametric innovations is proposed. We also design an improved technique to estimate the density of hea...
José Miguel Hernández-Lobato, Daniel...
SSDBM
2006
IEEE
167views Database» more  SSDBM 2006»
13 years 11 months ago
Exploring Data Streams with Nonparametric Estimators
A variety of real-world applications requires a meaningful online analysis of transient data streams. An important building block of many analysis tasks is the characterization of...
Christoph Heinz, Bernhard Seeger
ICASSP
2008
IEEE
14 years 2 days ago
Maximum kernel density estimator for robust fitting
Robust model fitting plays an important role in many computer vision applications. In this paper, we propose a new robust estimator — Maximum Kernel Density Estimator (MKDE) bas...
Hanzi Wang
ICIAR
2004
Springer
13 years 11 months ago
Nonparametric Impulsive Noise Removal
In this paper the problem of nonparametric impulsive noise removal in multichannel images is addressed. The proposed filter class is based on the nonparametric estimation of the d...
Bogdan Smolka, Rastislav Lukac