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» A finiteness theorem for Markov bases of hierarchical models
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ICIP
2007
IEEE
14 years 9 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...
WSC
1998
13 years 8 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
CVPR
2010
IEEE
13 years 10 months ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper
JMLR
2006
120views more  JMLR 2006»
13 years 7 months ago
Kernel-Based Learning of Hierarchical Multilabel Classification Models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Juho Rousu, Craig Saunders, Sándor Szedm&aa...
ISLPED
1997
ACM
104views Hardware» more  ISLPED 1997»
13 years 11 months ago
Composite sequence compaction for finite-state machines using block entropy and high-order Markov models
- The objective of this paper is to provide an effective technique for accurate modeling of the external input sequences that affect the behavior of Finite State Machines (FSMs). B...
Radu Marculescu, Diana Marculescu, Massoud Pedram