Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On Anomaly Interpretation via Shapley Values   Anomaly localization is an essential problem as anomaly detection is. Because
a rigorous localization requires a causal model of a target system, practically
we often resort to a relaxed problem of anomaly interpretation, for which we
are to obtain meaningful attribution of anomaly scores to input features. In
this paper, we investigate the use of the Shapley value for anomaly
interpretation. We focus on the semi-supervised anomaly detection and newly
propose a characteristic function, on which the Shapley value is computed,
specifically for anomaly scores. The idea of the proposed method is
approximating the absence of some features by minimizing an anomaly score with
regard to them. We examine the performance of the proposed method as well as
other general approaches to computing the Shapley value in interpreting anomaly
scores. We show the results of experiments on multiple datasets and anomaly
detection methods, which indicate the usefulness of the Shapley-based anomaly
interpretation toward anomaly localization.

19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
27
The categories of this paper are: comp-gas