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Nonnegative sparsity-constrained optimization problem arises in many fields, such as the linear compressing sensing problem and the regularized logistic regression cost function. In this paper, we introduce a new stepsize… Click to show full abstract
Nonnegative sparsity-constrained optimization problem arises in many fields, such as the linear compressing sensing problem and the regularized logistic regression cost function. In this paper, we introduce a new stepsize rule and establish a gradient projection algorithm. We also obtain some convergence results under milder conditions.
Keywords:
projection algorithm;
nonnegative sparsity;
new stepsize;
gradient projection;
constrained optimization;
sparsity constrained
Journal Title: Mathematical Problems in Engineering
Year Published: 2020
Link to full text (if available)
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Journal Title: Mathematical Problems in Engineering
Year Published: 2020
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!