Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multi-Domain Active Learning: A Comparative Study   Multi-domain learning (MDL) refers to learning a set of models
simultaneously, with each one specialized to perform a task in a certain
domain. Generally, high labeling effort is required in MDL, as data needs to be
labeled by human experts for every domain. To address the above issue, Active
learning (AL) can be utilized to reduce the labeling effort by only using the
most informative data. The resultant paradigm is termed multi-domain active
learning (MDAL). However, despite the practical significance of MDAL, there
exists little research on it, not to mention any off-the-shelf solution. To
fill this gap, we construct a simple pipeline of MDAL, and present a
comprehensive comparative study of 30 different MDAL algorithms, which are
established by combining 6 representative MDL models (equipped with various
information-sharing schemes) and 5 well-used AL strategies. We evaluate the
algorithms on 6 datasets, involving textual and visual classification tasks. In
most cases, AL brings notable improvements to MDL, and surprisingly, the naive
best vs second best (BvSB) uncertainty strategy could perform competitively to
the state-of-the-art AL strategies. Besides, among the MDL models, MAN and
SDL-joint achieve the top performance when applied to vector features and raw
images, respectively. Furthermore, we qualitatively analyze the behaviors of
these strategies and models, shedding light on their superior performance in
the comparison. Overall, some guidelines are provided, which could help to
choose MDL models and AL strategies for particular applications.

23
The categories of this paper are: solv-int
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph