Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Iterative regularization for convex regularizers   We study iterative regularization for linear models, when the bias is convex
but not necessarily strongly convex. We characterize the stability properties
of a primal-dual gradient based approach, analyzing its convergence in the
presence of worst case deterministic noise. As a main example, we specialize
and illustrate the results for the problem of robust sparse recovery. Key to
our analysis is a combination of ideas from regularization theory and
optimization in the presence of errors. Theoretical results are complemented by
experiments showing that state-of-the-art performances can be achieved with
considerable computational speed-ups.

20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph