Carl Edward Rasmussen  Home/Search
Context Related
| cmu.edu/Web/Groups/NIPS/...Rasmussen.ps Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: cmu.edu/Web/Groups/...99abstracts (more) Homepages: C.Rasmussen |
Rate this article:      (best)Comment on this article |
Abstract: In a Bayesian mixture model it is not necessary a priori to limit the number of components to be finite. In this paper an infinite Gaussian mixture model is presented which neatly sidesteps the difficult problem of finding the "right" number of mixture components. Inference in the model is done using an efficient parameter-free Markov Chain that relies entirely on Gibbs sampling. (Update)
Cited by: More
A Non-Parametric Bayesian Method for Inferring Hidden Causes - Frank Wood Computer (2006) (Correct)
A Non-Parametric Bayesian Approach to Spike Sorting - Frank Wood Sharon (2006) (Correct)
Hierarchical Dirichlet Processes - Yee Whye Teh (2003) (Correct)
Active bibliography (related documents): More All
1.3: Variational Inference for Dirichlet Process Mixtures - David M. Blei, Michael I.. (2006) (Correct)
0.1: The Infinite Gaussian Mixture Model - Rasmussen (2000) (Correct)
0.0: The Countably Infinite Bayesian Gaussian Mixture Density Model - Rasmussen (1999) (Correct)
Similar documents based on text: More All
0.2: Semiparametric Approach to Multichannel Blind Deconvolution.. - Zhang, Amari, al. (2000) (Correct)
0.1: Experiences with Matlab and VRML in Functional Neuroimaging.. - Nielsen, Hansen (2000) (Correct)
0.1: Teaching and learning with the WWW in the undergraduate.. - Oliver, Omari, Cowan (Correct)
Related documents from co-citation: More All
7: Markov chain sampling methods for Dirichlet process mixture models (context) - Neal - 1998
6: Bayesian density estimation and inference using mixtures - Escobar, West - 1994
5: Mixtures of Dirichlet processes with applications to Bayesian nonparametric prob.. (context) - Antoniak - 1974
BibTeX entry: (Update)
Rasmussen, C. E. (2000) The Infinite Gaussian Mixture Model, in S. A. Solla, T. K. Leen and K.-R. Muller (editors.), Adv. Neur. Inf. Proc. Sys. 12, MIT Press, pp. 554--560. http://citeseer.ist.psu.edu/rasmussen00infinite.html More
@misc{ rasmussen00infinite,
author = "C. Rasmussen",
title = "The Infinite Gaussian Mixture Model",
text = "Rasmussen, C. E. (2000) The Infinite Gaussian Mixture Model, in S. A. Solla,
T. K. Leen and K.-R. Muller (editors.), Adv. Neur. Inf. Proc. Sys. 12, MIT
Press, pp. 554--560.",
year = "2000",
url = "citeseer.ist.psu.edu/rasmussen00infinite.html" }
Citations (may not include all citations):269 Bayesian Learning for Neural Networks (context) - Neal - 1996
169 Mixtures of Dirichlet processes with applications to Bayesia.. (context) - Antoniak - 1974
168 A Bayesian analysis of some nonparametric problems (context) - Ferguson - 1973
150 On Bayesian analysis of mixtures with an unknown number of c.. - Richardson, Green - 1997
91 Adaptive rejection sampling for Gibbs sampling (context) - Gilks, Wild - 1992
78 Gaussian Processes for Regression - Williams - 1996
60 Markov chain sampling methods for Dirichlet process mixture .. (context) - Neal - 1998
41 SMEM Algorithm for Mixture Models - Ueda, Nakano et al. - 1998
16 Hierarchical priors and mixture models with applications in .. - West, Muller et al. - 1994
The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://www.cs.cmu.edu/Web/Groups/NIPS/1999/99abstracts.html): More
Can V1 mechanisms account for figure-ground and medial axis effects? - Li (2000) (Correct)
Boosting Algorithms as Gradient Descent - Mason, Baxter, al. (2000) (Correct)
The Relaxed Online Maximum Margin Algorithm - Li, Long (2000) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC