Minimax-Optimal Convergence Rates
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
... achieves minimax optimal convergence rates under relatively mild ...statistical minimax rate over all estimators using the set of N ...
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Minimax rates of convergence for Wasserstein deconvolution with supersmooth errors in any dimension
... (1) Laboratoire MAP5 UMR CNRS 8145, Universit´e Paris Descartes, Sorbonne Paris Cit´e, (2) Laboratoire de Statistique Th´eorique et Appliqu´ee, Universit´e Pierre et Marie Curie - Paris 6 Abstract The subject of this ...
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Optimal Rates of Convergence for Sparse Covariance Matrix Estimation
... Assouad’s lemma, Bregman divergence, covariance matrix estimation, Frobenius norm, Le Cam’s method, minimax lower bound, spectral norm, optimal rate of convergence, thresholding.... Many[r] ...
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Optimal Rates of Convergence for Estimating Toeplitz Covariance Matrices
... the optimal rate of convergence for estimating the inverse of a Toeplitz covariance ...establishing minimax lower ...A minimax lower bound for the more informative model, which immediately ...
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Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
... and convergence rates for the prediction error under certain conditions on the covariates as well as the sparsity s and dimension ...the rates obtained in these papers are sharp for the given ...
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Estimating Sparse Precision Matrix: Optimal Rates of Convergence and Adaptive Estimation
... the rates of convergence for the ACLIME esti- mator which provide upper bounds for the minimax ...the minimax rates of convergence is the derivation of rate sharp lower ...the ...
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Sparse functional regression models: minimax rates and contamination
... derive minimax convergence ...the minimax lower bound to the affinity to the total variation distance between the null and the alternative ...on minimax estimation in the functional data ...
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Optimal Rates of Convergence for Noisy Sparse Phase Retrieval via Thresholded Wirtinger Flow
... a minimax rate-optimal estimator and the thresholded power iteration serves as a heuristic algorithm for computing the sparsity constrained sample ...
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Optimal Rates of Convergence for Estimating the Null Density and Proportion of Nonnull Effects in Large-Scale Multiple Testing
... the minimax lower bound for estimating the null ...the minimax rates of convergence by showing that the lower bound is in fact ...the minimax estimation of the ...
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Minimax Rate-Optimal Estimation of High-Dimensional Covariance Matrices with Incomplete Data
... Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity ...
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Optimal Convergence Rates for Convex Distributed Optimization in Networks
... a convergence rate is achieved by the novel multi-step primal-dual (MSPD) algo- ...is optimal for smooth objective functions, and provide a simple yet efficient algorithm called distributed randomized ...
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Permutation estimation and minimax rates of identifiability
... The problem of matching two sets of features appears in various tasks of computer vision and can be often formalized as a problem of permutation estimation. We address this problem from a statistical point of view and ...
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Minimax Rates in Permutation Estimation for Feature Matching
... the minimax rate of separation is investigated and its expression is obtained as a function of the sample size, noise level and dimension of the ...the minimax rate increases with d and is of the order of ...
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Estimation of KL divergence: optimal minimax rate
... difficult to design joint prior distributions on (P, Q) that satisfy the above desired property. In order to simplify this procedure, we set one of the dis- tributions P and Q to be known. Then the minimax risk ...
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Learning locally minimax optimal Bayesian networks
... We consider the problem of learning Bayesian network models in a non-informative set- ting, where the only available information is a set of observational data, and no background knowledge is available. The problem can ...
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An isogeometric mortar method for the coupling of multiple NURBS domains with optimal convergence rates
... the convergence analysis are obtained by uniform ...expected convergence rates are obtained, even though the error level is higher for coarse ...
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Pricing Bermudan options using regression: Optimal rates of convergence for lower estimates
... e rates of { b C k,M } provided that α > 0 ...e rates of { b C k,M } are of order γ M −1/2 , the bias of V b 0,M onverges to zero as fast as γ M −(1+α)/2 ...
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Pricing Bermudan options using regression: optimal rates of convergence for lower estimates
... of convergence for regression algorithms have been already studied in several ...the convergence of the Longstaff-Schwartz ...the rates of convergence for continuation values estimates ...
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Rates of convergence to normality
... Chapter h provides analogues of the iterated logarithm law in the context of Galton-Watson processes, with or without immigration, fuch results had earlier been given under rather severe moment restrictions. In Chapter U ...
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Optimal Convergence Trading
... on optimal dynamic investments with risky ...(1973). Optimal investment in assets that follow a diffusion process with mean-reverting returns was ana- lyzed in Kim and Omberg (1996), Brennan et ...the ...
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