Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Improved Deterministic Rescaling for Linear Programming Algorithms   The perceptron algorithm for linear programming, arising from machine
learning, has been around since the 1950s. While not a polynomial-time
algorithm, it is useful in practice due to its simplicity and robustness. In
2004, Dunagan and Vempala showed that a randomized rescaling turns the
perceptron method into a polynomial time algorithm, and later Pe\~{n}a and
Soheili gave a deterministic rescaling. In this paper, we give a deterministic
rescaling for the perceptron algorithm that improves upon the previous
rescaling methods by making it possible to rescale much earlier. This results
in a faster running time for the rescaled perceptron algorithm. We will also
demonstrate that the same rescaling methods yield a polynomial time algorithm
based on the multiplicative weights update method. This draws a connection to
an area that has received a lot of recent attention in theoretical computer
science.

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The categories of this paper are: solv-int
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The categories of this paper are: q-bio
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The categories of this paper are: econ
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The categories of this paper are: stat
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
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The categories of this paper are: q-alg
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The categories of this paper are: q-fin
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The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: funct-an
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The categories of this paper are: cond-mat
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The categories of this paper are: mtrl-th