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For the Gaussian sequence model, we obtain non-asymptotic minimax rates of estimation of the linear, quadratic and the L2-norm functionals on classes of sparse vectors and construct optimal estimators that attain these rates.
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Classification of sparse high-dimensional vectors
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Nonparametric estimation via convex programming
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Introduction to Nonparametric Estimation
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Higher criticism for detecting sparse heterogeneous mixtures
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Exponential Screening and optimal rates of sparse estimation
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Minimax risks for sparse regressions: Ultra-high dimensional phenomenons
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Gaussian Estimation: Sequence and Wavelet Models
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