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» Inferring Mixtures of Markov Chains
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UAI
2000
15 years 1 months ago
Minimum Message Length Clustering Using Gibbs Sampling
The K-Means and EM algorithms are popular in clustering and mixture modeling due to their simplicity and ease of implementation. However, they have several significant limitations...
Ian Davidson
FGR
2008
IEEE
221views Biometrics» more  FGR 2008»
15 years 6 months ago
Markovian mixture face recognition with discriminative face alignment
A typical automatic face recognition system is composed of three parts: face detection, face alignment and face recognition. Conventionally, these three parts are processed in a b...
Ming Zhao 0003, Tat-Seng Chua
ICCV
2007
IEEE
16 years 1 months ago
Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes
We develop nonparametric Bayesian models for multiscale representations of images depicting natural scene categories. Individual features or wavelet coefficients are marginally de...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
IJCAI
2001
15 years 1 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
WSC
1998
15 years 1 months ago
Bayesian Model Selection when the Number of Components is Unknown
In simulation modeling and analysis, there are two situations where there is uncertainty about the number of parameters needed to specify a model. The first is in input modeling w...
Russell C. H. Cheng