Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Isometric sketching of any set via the Restricted Isometry Property   In this paper we show that for the purposes of dimensionality reduction
certain class of structured random matrices behave similarly to random Gaussian
matrices. This class includes several matrices for which matrix-vector multiply
can be computed in log-linear time, providing efficient dimensionality
reduction of general sets. In particular, we show that using such matrices any
set from high dimensions can be embedded into lower dimensions with near
optimal distortion. We obtain our results by connecting dimensionality
reduction of any set to dimensionality reduction of sparse vectors via a
chaining argument.

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The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
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The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
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The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
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The categories of this paper are: adap-org
0
The categories of this paper are: hep-ph
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The categories of this paper are: nlin