Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multiclass Diffuse Interface Models for Semi-Supervised Learning on
  Graphs   We present a graph-based variational algorithm for multiclass classification
of high-dimensional data, motivated by total variation techniques. The energy
functional is based on a diffuse interface model with a periodic potential. We
augment the model by introducing an alternative measure of smoothness that
preserves symmetry among the class labels. Through this modification of the
standard Laplacian, we construct an efficient multiclass method that allows for
sharp transitions between classes. The experimental results demonstrate that
our approach is competitive with the state of the art among other graph-based
algorithms.

21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
12
The categories of this paper are: nucl-th
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th