Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: More Efficient Sampling for Tensor Decomposition   Recent papers have developed alternating least squares (ALS) methods for CP
and tensor ring decomposition with a per-iteration cost which is sublinear in
the number of input tensor entries for low-rank decomposition. However, the
per-iteration cost of these methods still has an exponential dependence on the
number of tensor modes. In this paper, we propose sampling-based ALS methods
for the CP and tensor ring decompositions whose cost does not have this
exponential dependence, thereby significantly improving on the previous
state-of-the-art. We provide a detailed theoretical analysis and also apply the
methods in a feature extraction experiment.

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The categories of this paper are: math-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: atom-ph
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The categories of this paper are: q-bio
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: alg-geom
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The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-th
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The categories of this paper are: eess
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The categories of this paper are: stat