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» Dirichlet Process Mixtures of Generalized Linear Models
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BMCBI
2010
144views more  BMCBI 2010»
15 years 5 months ago
Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model
Background: Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is gen...
Xin He, Moushumi Sen Sarma, Xu Ling, Brant W. Chee...
NIPS
2007
15 years 6 months ago
Robust Regression with Twinned Gaussian Processes
We propose a Gaussian process (GP) framework for robust inference in which a GP prior on the mixing weights of a two-component noise model augments the standard process over laten...
Andrew Naish-Guzman, Sean B. Holden
WACV
2008
IEEE
15 years 11 months ago
Background Subtraction for Temporally Irregular Dynamic Textures
In the traditional mixture of Gaussians background model, the generating process of each pixel is modeled as a mixture of Gaussians over color. Unfortunately, this model performs ...
Gerald Dalley, Joshua Migdal, W. Eric L. Grimson
CSDA
2011
15 years 13 days ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland
ICML
2005
IEEE
16 years 6 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani