Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Minimax Rate"”.
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Estimation of KL divergence: optimal minimax rate
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms
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Consistency of nonparametric Bayesian methods for two statistical inverse problems arising from partial differential equations
… the true drift function, at the frequentist minimax rate (up to logarithmic factors) over periodic Besov smoothness classes. These conditions are verified for some natural nonparametric priors, some of which are shown to adapt to an unknown smoothness parameter. The results are given in the …
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Sparse functional regression models: minimax rates and contamination
… in estimating the sensitive point. The minimax rate of convergence for estimating the parameters in sparse functional linear regression is derived. It is shown that the optimal rate for estimating the sensitive point depends on the roughness of the predictor function, which is quantified …
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Scalable sparsity structure learning using Bayesian methods
… e.g., the corresponding posterior concentrates on balls with the desired minimax rate. Second, the above estimator could be directly applied to the high dimensional linear classification. In theory, we not only build a bridge to connect the estimation error of the mean difference and the …
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Model Selection, Uniform Inference and Nonparametric Regression
… An extensive Monte Carlo experiment corroborates the theoretical results by showing that the non-asymptotic bound becomes arbitrarily small as the sample size diverges. The second chapter returns to more classical statistics and econometrics by studying the uniform consistency of the series …
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Optimal estimation in high-dimensional and nonparametric models
Minimax optimality is a key property of an estimation procedure in statistical modelling. This thesis looks at several problems in high-dimensional and nonparametric statistics and proposes novel estimation procedures. It then provides statistical guarantees on the performance of these methods and …
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Some advances in Bayesian inference and generative modeling
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms