An accelerated minimal gradient method with momentum for strictly convex quadratic optimization
Sign Up to like & getrecommendations! Published in 2021 at "BIT Numerical Mathematics"
DOI: 10.1007/s10543-021-00886-9
Abstract: In this article we address the problem of minimizing a strictly convex quadratic function using a novel iterative method. The new algorithm is based on the well-known Nesterov’s accelerated gradient method. At each iteration of… read more here.
Keywords: strictly convex; accelerated minimal; gradient method; convex quadratic ... See more keywords
A simultaneous diagonalization based SOCP relaxation for convex quadratic programs with linear complementarity constraints
Sign Up to like & getrecommendations! Published in 2019 at "Optimization Letters"
DOI: 10.1007/s11590-018-1337-8
Abstract: This paper proposes a new second-order cone programming (SOCP) relaxation for convex quadratic programs with linear complementarity constraints. The new SOCP relaxation is derived by exploiting the technique that two positive semidefinite matrices can be… read more here.
Keywords: relaxation; linear complementarity; socp relaxation; complementarity constraints ... See more keywords
Special Issue dedicated to Workshop on Graph Spectra, Combinatorics and Optimization (WGSCO2018)
Sign Up to like & getrecommendations! Published in 2019 at "Optimization"
DOI: 10.1080/02331934.2020.1683315
Abstract: WGSCO 2018, Workshop on Graph Spectra, Combinatorics and Optimizationwas successfully held in the University of Aveiro, Portugal, at the occasion of the 65th birthday of Professor Domingos M. Cardoso. The topics of the Workshop reflected… read more here.
Keywords: convex quadratic; stability number; graph; optimization ... See more keywords