Abstract: Quadratic programming (QP) problems are common in many applications requiring optimization, including automatic control systems, finance analysis, chemical processes, etc. Typical QP ...
can be solved by solving an equivalent linear complementarity problem when H is positive semidefinite. The approach is outlined in the discussion of the LCP subroutine in Chapter 17, "Language ...
Abstract: A nonconvex-concave minimax quadratic problem is studied in this paper. An efficient alternating algorithm is proposed without any convexification procedures and constraint relaxations. By ...
PDHCG is a high-performance, GPU-accelerated implementation of the Primal-Dual Hybrid Gradient (PDHG) algorithm designed for solving large-scale Convex Quadratic Programming (QP) problems. For a ...
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