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Comparision of clustering methods for genetic networks
Comparision clustering methods genetic networks
2016/1/19
The goal of network clustering algorithms is to detect dense clusters in a network, which provides a first step towards the understanding of large scale biological networks. With numerous recent advan...
Monotonicity and Restart in Fast Gradient Methods
Monotonicity Restart Fast Gradient Methods
2015/7/9
Fast gradient methods are known to be non-monotone algorithms, and oscillations typically occur around the solution. To avoid this behavior, we propose in this paper a fast gradient method with restar...
First order optimization methods often perform poorly on ill-conditioned optimization problems. However, by preconditioning the problem data and solving the preconditioned problem, the performance of ...
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems
Validity Long-Run Estimation Methods Discrete-Event Systems
2015/7/8
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems.
Predicting the Severity of Breast Masses with Data Mining Methods
Breast cancer data mining decision tree neural network support vector machine
2013/6/17
Mammography is the most effective and available tool for breast cancer screening. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approxima...
Comparing composite likelihood methods based on pairs for spatial Gaussian random fieldsM
Covariance estimation Geostatistics Large datasets Tapering
2013/6/14
In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when...
Methods to Calculate the Upper Bound of Gini Coefficient Based on Grouped Data and the Result for China
Gini coefficient Grouped data Upper bound China
2013/6/14
How to give an upper bound, especially the smallest upper bound of Gini coefficient based on grouped data in the absence of income brackets is still a problem not properly solved. This article provide...
On the Complexity Analysis of Randomized Block-Coordinate Descent Methods
Randomized block-coordinate descent accelerated coordinate descent iteration complexity convergence rate composite minimization
2013/6/17
In this paper we analyze the randomized block-coordinate descent (RBCD) methods proposed in [8,11] for minimizing the sum of a smooth convex function and a block-separable convex function. In particul...
Fourier methods for smooth distribution function estimation
Fourier analysis kernel distribution estimation mean integrated squared error optimal bandwidth sinc kernel
2013/6/14
In this paper we show how to use Fourier transform methods to analyze the asymptotic behavior of kernel distribution function estimators. Exact expressions for the mean integrated squared error in ter...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...
The Estimation of Transport Logistic Processes Models on the Base of Intensive Computer Methods of Statistics
Transport Logistic Processes Models Intensive Computer Methods of Statistics
2013/6/13
The promotion work 'The Estimation of Transport Logistic Processes Models on the Base of Intensive Computer Methods of Statistics' has been worked out by Helen Afanasyeva to obtain the scientific degr...
Two General Methods for Population Pharmacokinetic Modeling: Non-Parametric Adaptive Grid and Non-Parametric Bayesian
Population pharmacokinetic modeling non-parametric maximum likelihood Bayesian Stick-breaking Pmetrics RJags
2013/5/2
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian...
On Sparsity Inducing Regularization Methods for Machine Learning
Sparsity Inducing Regularization Methods for Machine Learning
2013/5/2
During the past years there has been an explosion of interest in learning methods based on sparsity regularization. In this paper, we discuss a general class of such methods, in which the regularizer ...
Generalized Measures for the Evaluation of Community Detection Methods
Complex Networks Community Detection Evaluation Measure Cluster Analysis Purity Adjusted Rand Index Normalized Mutual Information
2013/5/2
Community detection can be considered as a variant of cluster analysis applied to complex networks. For this reason, all existing studies have been using tools derived from this field when evaluating ...