We are interested in approximation of a multivariate function
f(x1,…,xd) by linear combinations of products u1(x1)⋯ud(xd)
of univariate functions ui(xi), i=1,…,d. In the case d=2 it is a
classical problem of bilinear approximation. In the case of approximation in
the L2 space the bilinear approximation problem is closely related to the
problem of singular value decomposition (also called Schmidt expansion) of the
corresponding integral operator with the kernel f(x1,x2). There are known
results on the rate of decay of errors of best bilinear approximation in Lp
under different smoothness assumptions on f. The problem of multilinear
approximation (nonlinear tensor product approximation) in the case d≥3 is
more difficult and much less studied than the bilinear approximation problem.
We will present results on best multilinear approximation in Lp under mixed
smoothness assumption on f