Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Randomized projection methods for convex feasibility problems:
  conditioning and convergence rates   Finding a point in the intersection of a collection of closed convex sets,
that is the convex feasibility problem, represents the main modeling strategy
for many computational problems. In this paper we analyze new stochastic
reformulations of the convex feasibility problem in order to facilitate the
development of new algorithmic schemes. We also analyze the conditioning
problem parameters using certain (linear) regularity assumptions on the
individual convex sets. Then, we introduce a general random projection
algorithmic framework, which extends to the random settings many existing
projection schemes, designed for the general convex feasibility problem. Our
general random projection algorithm allows to project simultaneously on several
sets, thus providing great flexibility in matching the implementation of the
algorithm on the parallel architecture at hand. Based on the conditioning
parameters, besides the asymptotic convergence results, we also derive explicit
sublinear and linear convergence rates for this general algorithmic framework.

4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga