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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
ICANN
2009
Springer
13 years 11 months ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 2 days ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
TSP
2011
230views more  TSP 2011»
13 years 2 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
CSDA
2007
126views more  CSDA 2007»
13 years 7 months ago
A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...
Yongqiang Tang, Subhashis Ghosal