Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An adaptive gradient method for computing generalized tensor eigenpairs   High order tensor arises more and more often in signal processing,data
analysis, higher-order statistics, as well as imaging sciences. In this paper,
an adaptive gradient (AG) method is presented for generalized tensor
eigenpairs. Global convergence and linear convergence rate are established
under some suitable conditions. Numerical results are reported to illustrate
the efficiency of the proposed method. Comparing with the GEAP method, an
adaptive shifted power method proposed by Tamara G. Kolda and Jackson R. Mayo
[SIAM J. Matrix Anal. Appl., 35 (2014), pp. 1563-1581], the AG method is much
faster and could reach the largest eigenpair with a higher probability.

26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat