
Spatial Monte Carlo Integration with Annealed Importance Sampling
Evaluating expectations on a pairwise Boltzmann machine (PBM) (or Ising ...
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A Generalization of Spatial Monte Carlo Integration
Spatial Monte Carlo integration (SMCI) is an extension of standard Monte...
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Consistent Batch Normalization for Weighted Loss in ImbalancedData Environment
In this study, we consider classification problems based on neural netwo...
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Improvement of Batch Normalization in Imbalanced Data
In this study, we consider classification problems based on neural netwo...
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Empirical Bayes Method for Boltzmann Machines
In this study, we consider an empirical Bayes method for Boltzmann machi...
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Restricted Boltzmann Machine with Multivalued Hidden Variables: a model suppressing overfitting
Generalization is one of the most important issues in machine learning p...
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MomentumSpace Renormalization Group Transformation in Bayesian Image Modeling by Gaussian Graphical Model
A new Bayesian modeling method is proposed by combining the maximization...
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Susceptibility Propagation by Using Diagonal Consistency
A susceptibility propagation that is constructed by combining a belief p...
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LinearTime Algorithm in Bayesian Image Denoising based on Gaussian Markov Random Field
In this paper, we consider Bayesian image denoising based on a Gaussian ...
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Solving Nonparametric Inverse Problem in Continuous Markov Random Field using Loopy Belief Propagation
In this paper, we address the inverse problem, or the statistical machin...
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Effective MeanField Inference Method for Nonnegative Boltzmann Machines
Nonnegative Boltzmann machines (NNBMs) are recurrent probabilistic neura...
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MeanField Inference in Gaussian Restricted Boltzmann Machine
A Gaussian restricted Boltzmann machine (GRBM) is a Boltzmann machine de...
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Statistical Analysis of Loopy Belief Propagation in Random Fields
Loopy belief propagation (LBP), which is equivalent to the Bethe approxi...
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Inverse Renormalization Group Transformation in Bayesian Image Segmentations
A new Bayesian image segmentation algorithm is proposed by combining a l...
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BoltzmannMachine Learning of Prior Distributions of Binarized Natural Images
Prior distributions of binarized natural images are learned by using a B...
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Bayesian Reconstruction of Missing Observations
We focus on an interpolation method referred to Bayesian reconstruction ...
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Bayesian image segmentations by Potts prior and loopy belief propagation
This paper presents a Bayesian image segmentation model based on Potts p...
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Traffic data reconstruction based on Markov random field modeling
We consider the traffic data reconstruction problem. Suppose we have the...
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Muneki Yasuda
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Professor of Graduate School of Information Sciences at Tohoku University