A major enterprise in compressed sensing and sparse approximation is the design and analysis of computationally tractable algorithms for recovering sparse, exact or approximate, s...
Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner...
The exploitation of nested inequalities and surrogate constraints as originally proposed in Glover [Glover, F., 1965. A multiphase-dual algorithm for the zero–one integer progra...
Among all methods for reconstructing missing regions in a digital image, the so-called exemplar-based algorithms are very efficient and often produce striking results. They are ba...
Semidefinite Programming (SDP) may be seen as a generalization of Linear Programming (LP). In particular, one may extend interior point algorithms for LP to SDP, but it has proven...
Particle swarm optimization (PSO) has been in practice for more than 10 years now and has gained wide popularity in various optimization tasks. In the context to single objective ...