Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Blind Deconvolution by a Steepest Descent Algorithm on a Quotient
  Manifold   In this paper, we propose a Riemannian steepest descent method for solving a
blind deconvolution problem. We prove that the proposed algorithm with an
appropriate initialization will recover the exact solution with high
probability when the number of measurements is, up to log-factors, the
information-theoretical minimum scaling. The quotient structure in our
formulation yields a simpler penalty term in the cost function compared to
[LLSW16], which eases the convergence analysis and yields a natural
implementation. Empirically, the proposed algorithm has better performance than
the Wirtinger gradient descent algorithm and an alternating minimization
algorithm in the sense that i) it needs fewer operations, such as DFTs and
matrix-vector multiplications, to reach a similar accuracy, and ii) it has a
higher probability of successful recovery in synthetic tests. An image
deblurring problem is also used to demonstrate the efficiency and effectiveness
of the proposed algorithm.

37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg