Restricted Nonlinear Approximation

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Mathematical Methods for Supervised Learning (2005, background): “Any Besov space B q (Lp(X)) which is compactly embedded in C(X) is contained in Vθ with W0 = B s τ (Lτ )X)) with s arbitrarily large (see [8]).”
Greedy approximation (2008, methodology): “It was used in Cohen et al. (2000) for a description of approximation spaces defined in terms of {σm(f,Ψ)}.”
Harmonic analysis of the space BV. (2003, background): “Let us finally mention that the weak type estimates of Theorem 5.1 and Theorem 5.2 have equivalent formulations in terms of the approximation performance of thresholding procedures studied in [ 3 ].”
Best N Term Approximation Spaces for Tensor Product Wavelet Bases (2006, unknown): “∼� (2 j (α−1/q+1/2) cjk)� � q (N); see, e.g., [15] or [ 9 ].”
Maximal Spaces with Given Rate of Convergence for Thresholding Algorithms (2001, background): “Thus, V ∗ q can be viewed as a weak Besov space (V ∗ q = weakBs q (Lq )). For further discussion of thresholding and the spaces V ∗ q , we refer the reader to [ 2 ].”
Minimax or maxisets (2002, background): “These spaces prove to have a special importance in approximation theory (Cohen et al. 2000), coding (Donoho 1996) and estimation (Donoho and Johnstone, 1996).”
Greedy Approximation with Regard to Bases and General Minimal Systems (2002, background): “Further investigations ([22, 1, 13, 10]) showed that the concept of greedy bases is very useful in”