搜索结果: 1-15 共查到“理论统计学 convergence”相关记录96条 . 查询时间(0.125 秒)
Optimal Rates of Convergence of Transelliptical Component Analysis
Transelliptical component analysis Optimal rates of convergence Double asymptotics Minimax lower bound Elliptical copula
2013/6/14
Han and Liu (2012) proposed a method named transelliptical component analysis (TCA) for conducting scale-invariant principal component analysis on high dimensional data with transelliptical distributi...
When uniform weak convergence fails: empirical processes for dependence functions via epi- and hypographs
bootstrap copula epigraph hypograph stable tail dependence function minimum distance estimation weak convergence
2013/6/14
For copulas whose partial derivatives are not continuous everywhere on the interior of the unit cube, the empirical copula process does not converge weakly with respect to the supremum distance. This ...
Optimal rates of convergence for persistence diagrams in Topological Data Analysis
Optimal rates convergence persistence diagrams Topological Data Analysis
2013/6/14
Computational topology has recently known an important development toward data analysis, giving birth to the field of topological data analysis. Topological persistence, or persistent homology, appear...
On the Convergence and Consistency of the Blurring Mean-Shift Process
Mean-shift Convergence Consistency Clustering,γ-divergence Super robustness
2013/6/13
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shi...
The Convergence Rate of Majority Vote under Exchangeability
Convergence Rate Majority Vote Exchangeability
2013/4/28
Majority vote plays a fundamental role in many applications of statistics, such as ensemble classifiers, crowdsourcing, and elections. When using majority vote as a prediction rule, it is of basic int...
On the convergence of the IRLS algorithm in Non-Local Patch Regression
Non-local means non-local patch regression,ℓ p minimization non-convex optimization iteratively reweighted least-squares majorize-minimize stationary point relaxation sequence linear convergence
2013/4/28
Recently, it was demonstrated in [CS2012,CS2013] that the robustness of the classical Non-Local Means (NLM) algorithm [BCM2005] can be improved by incorporating $\ell^p (0 < p \leq 2)$ regression into...
The Rate of Convergence of AdaBoost
AdaBoost optimization coordinate descent convergence rate.
2011/7/7
The AdaBoost algorithm was designed to combine many "weak" hypotheses that perform slightly better than random guessing into a "strong" hypothesis that has very low error.
Convergence rate for predictive recursion estimation of finite mixtures
Density estimation Kullback–Leibler divergence
2011/7/6
Predictive recursion (PR) is a fast stochastic algorithm for nonparametric estimation of mixing distributions in mixture models.
Almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case
Kesten's stochastic approximation algorithm multidimensional
2011/6/20
It is shown the almost sure convergence and asymptotical normality of a generalization of
Kesten's stochastic approximation algorithm for multidimensional case.
In this generalization, the step incr...
Quantitative bounds for Markov chain convergence: Wasserstein and total variation distances
convergence rate coupling Gibbs sampler iterated random functions local
2011/3/24
We present a framework for obtaining explicit bounds on the rate of convergence to equilibrium of a Markov chain on a general state space, with respect to both total variation and Wasserstein distance...
Weak convergence of empirical copula processes under nonrestrictive smoothness assumptions
Statistics Theory (math.ST)
2010/12/17
Weak convergence of the empirical copula process is shown to hold under the assumption that the first-order partial derivatives of the copula exist and are continuous on certain subsets of the unit hy...
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...
A Bregman Extension of quasi-Newton updates II: Convergence and Robustness Properties
A Bregman Extension quasi-Newton updates II Convergence Robustness Properties
2010/10/19
We propose an extension of quasi-Newton methods, and investigate the convergence and the robustness properties of the proposed update formulae for the approximate Hessian matrix. Fletcher has studied ...
Operator norm convergence of spectral clustering on level sets
Spectral clustering graph unsupervised classification levelsets connected components
2010/3/10
Following Hartigan [1975], a cluster is defined as a connected component of
the t-level set of the underlying density, i.e., the set of points for which the
density is greater than t. A clustering a...
Convergence of U-statistics for interacting particle systems
interacting particle systems Feynman-Kac models U-statistics fluc-tuations limit theorems
2010/3/11
The convergence of U-statistics has been intensively studied for estimators based
on families of i.i.d. random variables and variants of them. In most cases, the indepen-
dence assumption is crucial...