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THE COMPARISON BETWEEN NMF AND ICA IN PIGMENT MIXTURE IDENTIFICATION OF ANCIENT CHINESE PAINTINGS
Hyperspectral Imaging Painting Relics Blind Source Separation Algorithm Non-negative Matrix Factorization Independent Component Analysis
2018/5/15
Since the colour in painting cultural relics observed by our naked eyes or hyperspectral cameras is usually a mixture of several kinds of pigments, the mixed pigments analysis will be an important sub...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/26
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/20
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Separating a Real-Life Nonlinear Image Mixture
independent component analysis source separation nonlinear image separation document processing
2015/8/3
When acquiring an image of a paper document, the image printed on the back page sometimes shows through. The mixture of the front- and back-page images thus obtained is markedly nonlinear, and thus co...
Proteomic analysis of plasma after branched chain enriched mixture supplementation in mice
Amino acids Proteome Dietary supplements
2015/7/27
Branched chain amino acid (BCAA) supplementation is a recently identified strategy to promote longevity in mice. A proteomic approach was used to identify proteins which are differentially expressed i...
Non-Negative Factor Analysis for Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition
Non-negative factor analysis model adaptation Gaussian mixture model weight dialect recognition language recognition
2014/11/27
Non-Negative Factor Analysis for Gaussian Mixture Model Weight Adaptation for Language and Dialect Recognition.
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Dynamic Clustering Asymptotics Dependent Dirichlet Process Mixture
2013/6/17
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The alg...
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering
Quantum annealing Dirichlet process Stochastic optimization Maximum a posteriori estimation Bayesian nonparametrics
2013/6/17
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP). QA is a parallelized extension of simulated annealing (SA)...
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
A Mixture of Generalized Hyperbolic Distributions
Mixture Generalized Hyperbolic Distributions
2013/6/13
We introduce a mixture of generalized hyperbolic distributions as an alternative to the ubiquitous mixture of Gaussian distributions as well as their near relatives of which the mixture of multivariat...
PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
Profile regression Clustering Dirichlet process mixture model
2013/4/27
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vect...
Capturing Patterns via Parsimonious t Mixture Models
Factor analysis Facial representation Image compression PGMM PTMM
2013/4/27
his paper exploits a simplified version of the mixture of multivariate t-factor analyzers (MtFA) for robust mixture modelling and clustering of high-dimensional data that frequently contain a number o...
Bayesian Mixture Models for Frequent Itemset Discovery
Bayesian Mixture Models Frequent Itemset Discovery
2012/11/26
In binary-transaction data-mining, traditional frequent itemset mining often produces results which are not straightforward to interpret. To overcome this problem, probability models are often used to...
Negative Binomial Process Count and Mixture Modeling
Negative Binomial Process Count and Mixture Modeling
2012/11/22
The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. We reveal relationships between the Poisson, multinomial, gamma and Dirichlet distrib...
Mixture Models for Single Cell Assays with Applications to Vaccine Studies
Mixture Models Single Cell Assays Applications to Vaccine Studies
2012/9/18
Blood and tissue are composed of many functionally distinct cell subsets. In immunological studies, these can only be measured accurately using single-cell assays. The characterization of these small ...