Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Learning Theoretic Perspective on Local Explainability   In this paper, we explore connections between interpretable machine learning
and learning theory through the lens of local approximation explanations.
First, we tackle the traditional problem of performance generalization and
bound the test-time accuracy of a model using a notion of how locally
explainable it is. Second, we explore the novel problem of explanation
generalization which is an important concern for a growing class of finite
sample-based local approximation explanations. Finally, we validate our
theoretical results empirically and show that they reflect what can be seen in
practice.

8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
30
The categories of this paper are: q-alg
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex