  We introduce a new, quadratically convergent algorithm for finding maximum
absolute value entries of tensors represented in the canonical format. The
computational complexity of the algorithm is linear in the dimension of the
tensor. We show how to use this algorithm to find global maxima of non-convex
multivariate functions in separated form. We demonstrate the performance of the
new algorithms on several examples.
