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10/27/2022
Multi-layered Discriminative Restricted Boltzmann Machine with Untrained Probabilistic Layer
An extreme learning machine (ELM) is a three-layered feed-forward neural...
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04/08/2022
Free Energy Evaluation Using Marginalized Annealed Importance Sampling
The evaluation of the free energy of a stochastic model is considered to...
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04/07/2022
Composite Spatial Monte Carlo Integration Based on Generalized Least Squares
Although evaluation of the expectations on the Ising model is essential ...
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12/21/2020
Spatial Monte Carlo Integration with Annealed Importance Sampling
Evaluating expectations on a pairwise Boltzmann machine (PBM) (or Ising ...
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09/04/2020
A Generalization of Spatial Monte Carlo Integration
Spatial Monte Carlo integration (SMCI) is an extension of standard Monte...
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01/06/2020
Consistent Batch Normalization for Weighted Loss in Imbalanced-Data Environment
In this study, we consider classification problems based on neural netwo...
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11/25/2019
Improvement of Batch Normalization in Imbalanced Data
In this study, we consider classification problems based on neural netwo...
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06/14/2019
Empirical Bayes Method for Boltzmann Machines
In this study, we consider an empirical Bayes method for Boltzmann machi...
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11/30/2018
Restricted Boltzmann Machine with Multivalued Hidden Variables: a model suppressing over-fitting
Generalization is one of the most important issues in machine learning p...
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03/20/2018
Momentum-Space 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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12/01/2017
Susceptibility Propagation by Using Diagonal Consistency
A susceptibility propagation that is constructed by combining a belief p...
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10/20/2017
Linear-Time 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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03/28/2017
Solving Non-parametric 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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03/08/2016
Effective Mean-Field Inference Method for Nonnegative Boltzmann Machines
Nonnegative Boltzmann machines (NNBMs) are recurrent probabilistic neura...
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12/03/2015
Mean-Field Inference in Gaussian Restricted Boltzmann Machine
A Gaussian restricted Boltzmann machine (GRBM) is a Boltzmann machine de...
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03/16/2015
Statistical Analysis of Loopy Belief Propagation in Random Fields
Loopy belief propagation (LBP), which is equivalent to the Bethe approxi...
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01/05/2015
Inverse Renormalization Group Transformation in Bayesian Image Segmentations
A new Bayesian image segmentation algorithm is proposed by combining a l...
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12/16/2014
Boltzmann-Machine Learning of Prior Distributions of Binarized Natural Images
Prior distributions of binarized natural images are learned by using a B...
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04/23/2014
Bayesian Reconstruction of Missing Observations
We focus on an interpolation method referred to Bayesian reconstruction ...
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04/11/2014
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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06/27/2013