convergence rates
Convergence rates for series estimators
... convergence rates for power series and regression spline estimators of projections on the. set & described in equation (2.3)[r] ...
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Convergence rates of the Heavy-Ball method for quasi-strongly convex optimization
... some convergence rates for the values F (x(t)) − F ∗ along the trajectories of the heavy ball ODE (2) for functions F having a unique minimizer and being quasi-strongly ...
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Convergence rates of the Heavy-Ball method with Lojasiewicz property
... minimize, convergence rates for convex functions, with some additional regularity such as quasi-strong convexity, or strong convexity, were recently obtained in ...[12]. Convergence results with much ...
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Support recovery and sup-norm convergence rates for sparse pivotal estimation
... In high dimensional sparse regression, pivotal estimators are estimators for which the opti- mal regularization parameter is independent of the noise level. The canonical pivotal es- timator is the square-root Lasso, ...
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On the ergodic convergence rates of a first-order primal-dual algorithm.
... a convergence theory, with more precise results, is found in ...paper convergence rates for the ADMM which are different from the ones currently found in the literature, see for instance ...
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Almost sure convergence rates for Stochastic Gradient Descent and Stochastic Heavy Ball
... sure convergence rates for SHB is quite involved, and combines tools developed in Attouch and Peypouquet ( 2016 ) for the analysis of the (deterministic) Nesterov Accelerated Gradient method and the ...
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Convergence rates for density estimators of weakly dependent time series
... uniform convergence rates (Theorems 2 and 3) is due to the fact that the probability inequalities for dependent observations are not as good as Bernstein’s inequality for ...The convergence ...
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Convergence rates for nonequilibrium Langevin dynamics
... the convergence rates in terms of the parameters of the dynamics; see for instance [13] for the Hamiltonian limit ξ → 0 and [19, 21] for partial results on the overdamped limit ξ → ...the convergence ...
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Convergence rates with singular parameterizations for solving elliptic boundary value problems in isogeometric analysis
... In this paper, we present the convergence rates for solving elliptic boundary value problems with singular parameterizations. Recently, there are works focused on singular parameterizations in the IGA. In ...
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Asymptotic convergence rates of SWR methods for Schrödinger equations with an arbitrary number of subdomains
... asymptotic convergence rate ...of convergence of some SWR methods by using an arbitrary number of ...the convergence of SWR algorithms on 2 subdomains [6, 7, ...the convergence rates ...
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Enhanced convergence rates and asymptotics for a dispersive Boussinesq-type system with large ill-prepared data
... Let us also mention works in the periodic case where resonences have to be studied (see for example [24, 40, 41, 43]), in the rotating fluids system case (see [16, 17, 18, 26, 28, 36]) or in the inviscid case (see [22, ...
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Analysis of correlations and their impact on convergence rates in Monte Carlo eigenvalue simulations
... its convergence rate during the power iteration process and seek to develop some intuition on how best to assign computational resources in evaluating problems with large correlations starting from a stationary ...
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Computable Convergence Rates for Subgeometrically Ergodic Markov Chains
... realistic conditions may be obtained by using small sets associated to the iterate P m of the kernel (see e.g. Rosenthal (1995), Fort (2001) and Fort and Moulines (2003b)). 2.1. Stochastically ordered chains. In this ...
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On the Convergence Rates of Proximal Splitting Algorithms
... A special class of nonexpansive operators is the α– averaged operators [7] for α ∈]0, 1[. The above two com- plexity bounds obviously apply, where now λ k ∈]0, α 1 [ and condition Theorem (b) is changed accordingly. 3. ...
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On Convergence Rates of Empirical Bayes Procedures
... contraction rates of empirical Bayes posterior distributions can be obtained as a refinement of Proposition 3 in ...contraction rates in the context of linear regression with unknown error distribution that ...
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Influence of sampling on the convergence rates of greedy algorithms for parameter-dependent random variables
... [7] Annalisa Buffa, Yvon Maday, Anthony T Patera, Christophe Prud’homme, and Gabriel Turinici. A priori convergence of the greedy algorithm for the parametrized reduced basis method. ESAIM: Math- ematical ...
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Convergence rates & asymptotic normality for series estimators
... This paper has derived convergence rate and asymptotic normality results for series. estimators[r] ...
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Convergence rates of Gibbs measures with degenerate minimum
... We generally assume f to be coercive, i.e. f(x) → +∞ as ||x|| → +∞, C 2p in a neighbourhood of x ? for some p ∈ N and we assume that the minimum is polynomial strict, i.e. the function f is bounded below in a ...
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Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density
... concentration rates of the posterior distributions under specific types of priors corresponding to different mixtures of ...obtain convergence rates for maximum likelihood ...
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Rates of convergence for the posterior distributions of mixtures of Betas and adaptive nonparametric estimation of the density
... concentration rates of the posterior distributions under specific types of priors corresponding to different mixtures of ...obtain convergence rates for maximum likelihood ...
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