217 search results - page 12 / 44 » Incremental learning of nonparametric Bayesian mixture model... |
ICASSP
2011
IEEE
14 years 1 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
NIPS
2004
14 years 11 months ago
2004
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
SIGIR
2004
ACM
15 years 2 months ago
2004
ACM
Information filtering has made considerable progress in recent years.The predominant approaches are content-based methods and collaborative methods. Researchers have largely conc...
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ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
JMLR
2012
12 years 12 months ago
2012
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...