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$l_{2,p}$ Matrix Norm and Its Application in Feature Selection
$l_{2,p}$ Matrix Norm Its Application Feature Selection
2013/5/2
Recently, $l_{2,1}$ matrix norm has been widely applied to many areas such as computer vision, pattern recognition, biological study and etc. As an extension of $l_1$ vector norm, the mixed $l_{2,1}$ ...
Variational Semi-blind Sparse Deconvolution with Orthogonal Kernel Bases and its Application to MRFM
Variational Bayesian inference posterior image distribution image reconstruction hyperparameter estimation MRFM experiment
2013/5/2
We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known. To solve this semi-blind d...
A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models
Population Monte Carlo importance sampling degeneracy of importance weights stochastic kinetic models
2012/9/18
This paper addresses the problem of Monte Carlo approximation of posterior probability distributions. In particular, we have considered a recently proposed technique known as population Monte Carlo (P...
Adaptive Markov Chain Monte Carlo for Auxiliary Variable Method and Its Application to Parallel Tempering
Adaptive Markov Chain Monte Carlo Auxiliary Variable Method Parallel Tempering Conver-gence
2012/9/19
Auxiliary variable methods such as the Parallel Tempering and the cluster Monte Carlo methods generate samples that follow a target distri-bution by using proposal and auxiliary distributions.In sampl...
Laplace deconvolution and its application to Dynamic Contrast Enhanced imaging
Laplace deconvolution complexity penalty Dynamic Contrast Enhanced imaging
2012/9/19
In the present paper we consider the problem of Laplace deconvolution with noisy discrete observations. The study is motivated by Dynamic Contrast Enhanced imaging using a bolus of contrast agent, a p...
Closed-Form EM for Sparse Coding and Its Application to Source Separation
Closed-Form EM Sparse Coding Source Separation
2011/6/17
We define and discuss the first sparse coding algorithm based on closed-form EM
updates and continuous latent variables. The underlying generativemodel consists
of a flexibly parameterized ‘spike-an...
Graver basis for an undirected graph and its application to testing the beta model of random graphs
Markov basis Markov chain Monte Carlo Rasch model toric ideal
2011/3/21
In this paper we give an explicit and algorithmic description of Graver basis for the toric ideal associated with a simple undirected graph and apply the basis for testing the beta model of random gra...
Weak Convergence of Markov Chain Monte Carlo Methods and its Application to Regular Gibbs Sampler
Methodology (stat.ME) Statistics Theory (math.ST)
2010/12/17
In this paper, we introduce the notion of efficiency (consistency) and examine some asymptotic properties of Markov chain Monte Carlo methods. We apply these results to the Gibbs sampler for independe...