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SSPR
2010
Springer
13 years 5 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
NIPS
2007
13 years 9 months ago
Non-parametric Modeling of Partially Ranked Data
Statistical models on full and partial rankings of n items are often of limited practical use for large n due to computational consideration. We explore the use of non-parametric ...
Guy Lebanon, Yi Mao
CVPR
2008
IEEE
14 years 9 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
ICPR
2002
IEEE
14 years 8 months ago
Bayesian Rendering with Non-Parametric Multiscale Prior Model
This paper investigates the use of the Bayesian inference for devising an example-based rendering procedure. As prior model of this Bayesian inference, we exploit the multiscale n...
Max Mignotte
ISIPTA
2005
IEEE
162views Mathematics» more  ISIPTA 2005»
14 years 1 months ago
Learning from multinomial data: a nonparametric predictive alternative to the Imprecise Dirichlet Model
A new model for learning from multinomial data has recently been developed, giving predictive inferences in the form of lower and upper probabilities for a future observation. Apa...
Frank P. A. Coolen, Thomas Augustin