Hard-thresholding-based algorithms have seen various advantages for sparse optimization in controlling the sparsity and allowing fast computation. Recent research shows that when techniques of Newton-type methods are integrated, their numerical performance can be improved surprisingly. This paper develops a gradient projection Newton pursuit algorithm mainly adopts hard-thresholding operator em...

background: sperm selection for icsi based on morphology and motility might not be relevant to chromatin integrity. thus sperm selection based on sperm characteristics has been suggested. objective: the aim of this study was to compare the efficiency of zeta method with routine density gradient centrifugation method (dgc) for the selection of sperm with higher dna integrity. materials and metho...

The objective of this work is to derive a Mixed Integer Quadratic Programming algorithm tailored for Model Predictive Control for hybrid systems. The Mixed Integer Quadratic Programming algorithm is built on the branch and bound method, where Quadratic Programming relaxations of the original problem are solved in the nodes of a binary search tree. The difference between these subproblems is oft...

In this paper we improve traditional steepest descent methods for the direct minimization of the Gross-Pitaevskii (GP) energy with rotation at two levels. We first define a new inner product to equip the Sobolev space H1 and derive the corresponding gradient. Secondly, for the treatment of the mass conservation constraint, we use a new projection method that avoids more complicated approaches b...

We consider a large-scale convex minimization problem with nonnegativity constraints that arises in astronomical imaging. We develop a cost functional which incorporates the statistics of the noise in the image data and Tikhonov regularization to induce stability. We introduce an efficient hybrid gradient projection-reduced Newton (active set) method. By “reduced Newton” we mean taking Newton s...

This paper is concerned with some new projection methods for solving variational inequality problems with monotone and Lipschitz-continuous mapping in Hilbert space. First, we propose the projected reflected gradient algorithm with a constant stepsize. It is similar to the projected gradient method, namely, the method requires only one projection onto the feasible set and only one value of the ...