Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MVG Mechanism: Differential Privacy under Matrix-Valued Query   Differential privacy mechanism design has traditionally been tailored for a
scalar-valued query function. Although many mechanisms such as the Laplace and
Gaussian mechanisms can be extended to a matrix-valued query function by adding
i.i.d. noise to each element of the matrix, this method is often suboptimal as
it forfeits an opportunity to exploit the structural characteristics typically
associated with matrix analysis. To address this challenge, we propose a novel
differential privacy mechanism called the Matrix-Variate Gaussian (MVG)
mechanism, which adds a matrix-valued noise drawn from a matrix-variate
Gaussian distribution, and we rigorously prove that the MVG mechanism preserves
$(\epsilon,\delta)$-differential privacy. Furthermore, we introduce the concept
of directional noise made possible by the design of the MVG mechanism.
Directional noise allows the impact of the noise on the utility of the
matrix-valued query function to be moderated. Finally, we experimentally
demonstrate the performance of our mechanism using three matrix-valued queries
on three privacy-sensitive datasets. We find that the MVG mechanism notably
outperforms four previous state-of-the-art approaches, and provides comparable
utility to the non-private baseline.

15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: funct-an