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Many asymptotically minimax procedures for function estimation often rely on somewhat arbitrary and restrictive assumptions such as isotropy or spatial homogeneity.
Multidimensional binary search trees in database applications
J. L. Bentley · 1979
Earlier work this paper cites.
Statistical Estimation: Asymptotic Theory
I. A. Ibragimov and R. Z. Hasminskii · 1981
Earlier work this paper cites.
Spline smoothing in regression models and asymptotic efficiency in L 2 {L}_{2}
M. Nussbaum · 1985
Earlier work this paper cites.
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L. Birgé · 1986
Earlier work this paper cites.
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J. H. Albert and S. Chib · 1993
Earlier work this paper cites.
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L. Birgé and P. Massart · 1993
Earlier work this paper cites.
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P. J. Green · 1995
Earlier work this paper cites.
Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
W. H. Wong and X. Shen · 1995
Earlier work this paper cites.
Weak Convergence and Empirical Processes
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Earlier work this paper cites.
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D. L. Donoho · 1997
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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