Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous
  Graphs   Graph neural networks have shown superior performance in a wide range of
applications providing a powerful representation of graph-structured data.
Recent works show that the representation can be further improved by auxiliary
tasks. However, the auxiliary tasks for heterogeneous graphs, which contain
rich semantic information with various types of nodes and edges, have less
explored in the literature. In this paper, to learn graph neural networks on
heterogeneous graphs we propose a novel self-supervised auxiliary learning
method using meta-paths, which are composite relations of multiple edge types.
Our proposed method is learning to learn a primary task by predicting
meta-paths as auxiliary tasks. This can be viewed as a type of meta-learning.
The proposed method can identify an effective combination of auxiliary tasks
and automatically balance them to improve the primary task. Our methods can be
applied to any graph neural networks in a plug-in manner without manual
labeling or additional data. The experiments demonstrate that the proposed
method consistently improves the performance of link prediction and node
classification on heterogeneous graphs.

12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat