Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Entropy Regularized Iterative Weighted Shrinkage-Thresholding Algorithm
  (ERIWSTA): An Application to CT Image Restoration   The iterative weighted shrinkage-thresholding algorithm (IWSTA) has shown
superiority to the classic unweighted iterative shrinkage-thresholding
algorithm (ISTA) for solving linear inverse problems, which address the
attributes differently. This paper proposes a new entropy regularized IWSTA
(ERIWSTA) that adds an entropy regularizer to the cost function to measure the
uncertainty of the weights to stimulate attributes to participate in problem
solving. Then, the weights are solved with a Lagrange multiplier method to
obtain a simple iterative update. The weights can be explained as the
probability of the contribution of an attribute to the problem solution.
Experimental results on CT image restoration show that the proposed method has
better performance in terms of convergence speed and restoration accuracy than
the existing methods.

26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat