mlsanityData to 14 Oct 2026

The Complexity of Computing KKT Solutions of Quadratic Programs

arXiv 2311.13738 ↗First posted 22 Nov 2023cs.CC math.OCcited by 4

Not on the map. Why?

Abstract (arXiv)

It is well known that solving a (non-convex) quadratic program is NP-hard. We show that the problem remains hard even if we are only looking for a Karush-Kuhn-Tucker (KKT) point, instead of a global optimum. Namely, we prove that computing a KKT point of a quadratic polynomial over the domain [0,1]n is complete for the class CLS = PPADcapPLS.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Nov 2023.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 2.

4 papers.