Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AAANE: Attention-based Adversarial Autoencoder for Multi-scale Network
  Embedding   Network embedding represents nodes in a continuous vector space and preserves
structure information from the Network. Existing methods usually adopt a
"one-size-fits-all" approach when concerning multi-scale structure information,
such as first- and second-order proximity of nodes, ignoring the fact that
different scales play different roles in the embedding learning. In this paper,
we propose an Attention-based Adversarial Autoencoder Network Embedding(AAANE)
framework, which promotes the collaboration of different scales and lets them
vote for robust representations. The proposed AAANE consists of two components:
1) Attention-based autoencoder effectively capture the highly non-linear
network structure, which can de-emphasize irrelevant scales during training. 2)
An adversarial regularization guides the autoencoder learn robust
representations by matching the posterior distribution of the latent embeddings
to given prior distribution. This is the first attempt to introduce attention
mechanisms to multi-scale network embedding. Experimental results on real-world
networks show that our learned attention parameters are different for every
network and the proposed approach outperforms existing state-of-the-art
approaches for network embedding.

18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph