Min-Max Grassmannian Optimization for Online Subspace Tracking

arXiv:2604.00825 · eess.SY, cs.SY, math.OC · Submitted 2026-04-01 · Read on arXiv

eess.SY, cs.SY, math.OC

Submitted: 2026-04-01

Updated: 2026-09-22

Code: https://github.com/shreyasnb/gerost

Terminology

• Robustness — 10× in this paper · explained in 5 episodes
• Spectral Gap — 7× in this paper · explained in 5 episodes
• AUC — 6× in this paper · explained in 2 episodes
• Convergence Guarantees — 6× in this paper · explained in 3 episodes
• System Identification — 5× in this paper · explained in 3 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Ambient Dimension — 2× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Stiefel manifold — 1× in this paper · explained in 2 episodes

Sources

• ReProCS: A Missing Link between Recursive Robust PCA and Recursive Sparse Recovery in Large but Correlated Noise
• Online Subspace Learning on Flag Manifolds for System Identification
• Geometrically robust least squares through manifold optimization
• Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
• Simple algorithms for optimization on Riemannian manifolds with constraints

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