Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Interferometric Graph Transform for Community Labeling   We present a new approach for learning unsupervised node representations in
community graphs. We significantly extend the Interferometric Graph Transform
(IGT) to community labeling: this non-linear operator iteratively extracts
features that take advantage of the graph topology through demodulation
operations. An unsupervised feature extraction step cascades modulus
non-linearity with linear operators that aim at building relevant invariants
for community labeling. Via a simplified model, we show that the IGT
concentrates around the E-IGT: those two representations are related through
some ergodicity properties. Experiments on community labeling tasks show that
this unsupervised representation achieves performances at the level of the
state of the art on the standard and challenging datasets Cora, Citeseer,
Pubmed and WikiCS.

37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph