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A Markov Chain Perspective on Adaptive Monte Carlo Algorithms
Markov Chain Perspective Adaptive Monte Carlo Algorithms
2015/7/8
This paper discusses some connections between adaptive Monte Carlo algorithms and general state space Markov chains. Adaptive algorithms are iterative methods in which previously generated samples are...
A Large Deviations Perspective on Ordinal Optimization
Large Deviations Perspective Ordinal Optimization
2015/7/6
We consider the problem of optimal allocation of computing budget to maximize the probability of correct selection in the ordinal optimization setting. This problem has been studied in the literature ...
Covariance inflation in the ensemble Kalman filter: a residual nudging perspective and some implications
Covariance inflation ensemble Kalman filter residual nudging perspective some implications
2013/6/17
This note examines the influence of covariance inflation on the distance between the measured observation and the simulated (or predicted) observation with respect to the state estimate. In order for ...
Self-configuration from a Machine-Learning Perspective
Machine-Learning Perspective Self-configuration Sequen-tial Parameter Optimization
2011/6/21
The goal of machine learning is to provide solutions which are trained by data
or by experience coming from the environment. Many training algorithms exist and
some brilliant successes were achieved...
Multiway Spectral Clustering: A Margin-Based Perspective
Spectral clustering spectral relaxation graph partitioning reproducing kernel Hilbert space large-margin classifi ca-tion Gaussian intrinsic autoregression
2011/3/22
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector problem, and in whi...
Multiway Spectral Clustering: A Margin-Based Perspective
Spectral clustering spectral relaxation graph partitioning reproducing kernel Hilbert space large-margin classifi ca-tion Gaussian intrinsic autoregression
2011/3/23
Spectral clustering is a broad class of clustering procedures in which an intractable combinatorial optimization formulation of clustering is "relaxed" into a tractable eigenvector problem, and in whi...
EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective
hidden Markov model incomplete data missing data EM trans-dimensional Monte Carlo computational statistics
2009/9/22
Hidden Markov models (HMMs) and related models have become stan-
dard in statistics during the last 15C2 years, with applications in diverse areas
like speech and other statistical signal processing...
Bivariate Ordinal Data in the Perspective of the Wisconsin Epidemiologic Study of Diabetic Retinopathy: Different Statistical Directions
Bivariate Ordinal Data Diabetic Retinopathy Different Statistical Directions
2009/9/17
Bivariate Ordinal Data in the Perspective of the Wisconsin Epidemiologic Study of Diabetic Retinopathy: Different Statistical Directions。
Multivariate Statistical Analysis：A Geometric Perspective
Multivariate Statistical Analysis Geometric Perspective
2010/3/18
Linear statistical analysis, and the least squares method specifically, achieved
their modern complete form in the language of linear algebra, that is in the
language of geometry. In this article we...
We consider the problem of detecting edges in piecewise
smooth functions from their N-degree spectral content, which is assumed
to be corrupted by noise. There are three scales involved: the
“smoot...