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» Semi-Supervised Learning of Mixture Models
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158
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ICIP
2007
IEEE
16 years 4 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
133
Voted
ICML
2005
IEEE
16 years 3 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
NIPS
2008
15 years 4 months ago
Implicit Mixtures of Restricted Boltzmann Machines
We present a mixture model whose components are Restricted Boltzmann Machines (RBMs). This possibility has not been considered before because computing the partition function of a...
Vinod Nair, Geoffrey E. Hinton
102
Voted
SETN
2004
Springer
15 years 8 months ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
129
Voted
DAGM
2010
Springer
15 years 3 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen