Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A label efficient two-sample test   Two-sample tests evaluate whether two samples are realizations of the same
distribution (the null hypothesis) or two different distributions (the
alternative hypothesis). In the traditional formulation of this problem, the
statistician has access to both the measurements (feature variables) and the
group variable (label variable). However, in several important applications,
feature variables can be easily measured but the binary label variable is
unknown and costly to obtain. In this paper, we consider this important
variation on the classical two-sample test problem and pose it as a problem of
obtaining the labels of only a small number of samples in service of performing
a two-sample test. We devise a label efficient three-stage framework: firstly,
a classifier is trained with samples uniformly labeled to model the posterior
probabilities of the labels; secondly, a novel query scheme dubbed
\emph{bimodal query} is used to query labels of samples from both classes with
maximum posterior probabilities, and lastly, the classical Friedman-Rafsky (FR)
two-sample test is performed on the queried samples. Our theoretical analysis
shows that bimodal query is optimal for two-sample testing using the FR
statistic under reasonable conditions and that the three-stage framework
controls the Type I error. Extensive experiments performed on synthetic,
benchmark, and application-specific datasets demonstrate that the three-stage
framework has decreased Type II error over uniform querying and certainty-based
querying with same number of labels while controlling the Type I error. Source
code for our algorithms and experimental results is available at
https://github.com/wayne0908/Label-Efficient-Two-Sample.

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The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
37
The categories of this paper are: supr-con
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The categories of this paper are: bayes-an
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The categories of this paper are: comp-gas
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
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The categories of this paper are: ao-sci
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ex
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg