On minimax density estimation on R

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Adaptive density estimation: a curse of support? ✩ (2009, methodology): “The subsequent results will constitute generalizations of the results derived in Juditsky and Lambert-Lacroix (2004) who pointed out minimax rates for density estimation on the class of Hölder spaces.”
An exponential inequality for the distribution function of the kernel density estimator, with applications to adaptive estimation (2009, methodology): “, [7,19,21,22], the case p = ∞ does not seem to have been treated in the literature, except in the context of the Gaussian white noise model: Using Lepski’s method, Tsybakov [33] treated the case p = ∞ as well as pointwise density estimation in this Gaussian framework, and using an estimator differe”
Adaptation on the space of finite signed measures (2008, background): “For example, Donoho, Johnstone, Kerkyacharian, Picard (1996), Kerkyacharian, Picard, Tribouley (1996) (for compactly supported densities) and Juditsky and Lambert-Lacroix (2004) (for densities on R) treated adaptation in general Lp-loss, 1 ≤ p ∞, for compactly supported densities, by…”
Near optimal thresholding estimation of a Poisson intensity on the real line (2008, methodology): “First general results where the loss is independent of the functional class have been pointed out by Juditsky and Lambert-Lacroix [29] who investigated minimax rates on the particular class of the Besov spaces Bα∞,∞ for the Lp′ -risk.”