May 18 – 22, 2026
Virginia Tech
America/New_York timezone

Stiefel Optimization is NP-hard

May 21, 2026, 11:25 AM
25m
Goodwin Hall 135

Goodwin Hall 135

Minisymposium Talk Matrix Geometries Matrix Geometries

Speaker

Dr Tianyun Tang (University of Chicago)

Description

We show that linearly constrained linear optimization over a Stiefel or Grassmann manifold is NP-hard in general. We show that the same is true for unconstrained quadratic opti- mization over a Stiefel manifold. We will show that unless P = NP, these optimization problems over a Stiefel manifold do not have FPTAS. As an aside we extend our results to flag manifolds. Combined with earlier findings, this shows that manifold optimization is a difficult endeavor — even the simplest problems like LP and unconstrained QP are already NP-hard on the most common manifolds.

Authors

Prof. Lek-Heng Lim (The University of Chicago) Dr Zehua Lai (University of Texas at Austin)

Presentation materials

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