Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: When in Doubt: Improving Classification Performance with Alternating
  Normalization   We introduce Classification with Alternating Normalization (CAN), a
non-parametric post-processing step for classification. CAN improves
classification accuracy for challenging examples by re-adjusting their
predicted class probability distribution using the predicted class
distributions of high-confidence validation examples. CAN is easily applicable
to any probabilistic classifier, with minimal computation overhead. We analyze
the properties of CAN using simulated experiments, and empirically demonstrate
its effectiveness across a diverse set of classification tasks.

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The categories of this paper are: ao-sci
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The categories of this paper are: acc-phys
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The categories of this paper are: econ
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The categories of this paper are: hep-ph
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The categories of this paper are: funct-an
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The categories of this paper are: q-alg
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The categories of this paper are: hep-ex
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The categories of this paper are: comp-gas
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The categories of this paper are: adap-org
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The categories of this paper are: dg-ga
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The categories of this paper are: gr-qc
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The categories of this paper are: patt-sol
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The categories of this paper are: mtrl-th
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The categories of this paper are: astro-ph
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The categories of this paper are: math
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The categories of this paper are: cond-mat