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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 ...
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...
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...