Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An unexpected connection between Bayes $A-$optimal designs and the Group
  Lasso   We show that the $A$-optimal design optimization problem over $m$ design
points in $\mathbb{R}^n$ is equivalent to minimizing a quadratic function plus
a group lasso sparsity inducing term over $n\times m$ real matrices. This
observation allows to describe several new algorithms for $A$-optimal design
based on splitting and block coordinate decomposition. These techniques are
well known and proved powerful to treat large scale problems in machine
learning and signal processing communities. The proposed algorithms come with
rigorous convergence guaranties and convergence rate estimate stemming from the
optimization literature. Performances are illustrated on synthetic benchmarks
and compared to existing methods for solving the optimal design problem.

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The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
1
The categories of this paper are: cs
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics