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SSPR
2010
Springer
15 years 2 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
15 years 6 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
16 years 6 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
16 years 5 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»
15 years 10 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