Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Convergence of a greedy algorithm for high-dimensional convex nonlinear
  problems   In this article, we present a greedy algorithm based on a tensor product
decomposition, whose aim is to compute the global minimum of a strongly convex
energy functional. We prove the convergence of our method provided that the
gradient of the energy is Lipschitz on bounded sets. The main interest of this
method is that it can be used for high-dimensional nonlinear convex problems.
We illustrate this method on a prototypical example for uncertainty propagation
on the obstacle problem.

10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
31
The categories of this paper are: ao-sci