Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Active Learning via Open Set Recognition   In many applications, data is easy to acquire but expensive and
time-consuming to label prominent examples include medical imaging and NLP.
This disparity has only grown in recent years as our ability to collect data
improves. Under these constraints, it makes sense to select only the most
informative instances from the unlabeled pool and request an oracle (e.g., a
human expert) to provide labels for those samples. The goal of active learning
is to infer the informativeness of unlabeled samples so as to minimize the
number of requests to the oracle. Here, we formulate active learning as an
open-set recognition problem. In this paradigm, only some of the inputs belong
to known classes; the classifier must identify the rest as unknown. More
specifically, we leverage variational neural networks (VNNs), which produce
high-confidence (i.e., low-entropy) predictions only for inputs that closely
resemble the training data. We use the inverse of this confidence measure to
select the samples that the oracle should label. Intuitively, unlabeled samples
that the VNN is uncertain about are more informative for future training. We
carried out an extensive evaluation of our novel, probabilistic formulation of
active learning, achieving state-of-the-art results on MNIST, CIFAR-10, and
CIFAR-100. Additionally, unlike current active learning methods, our algorithm
can learn tasks without the need for task labels. As our experiments show, when
the unlabeled pool consists of a mixture of samples from multiple datasets, our
approach can automatically distinguish between samples from seen vs. unseen
tasks.

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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
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The categories of this paper are: hep-th
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The categories of this paper are: solv-int
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The categories of this paper are: physics
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The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
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The categories of this paper are: econ
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: q-bio
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The categories of this paper are: nlin
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The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat