arXiv cs.AI
· Papers
Retraction-Free Optimization over the Stiefel Manifold for the LoRA Fine-Tuning
arXiv:2607.25299v1 Announce Type: cross Abstract: Optimization over the Stiefel manifold plays a significant role in various machine learning tasks. Existing methods either use the retraction operators, requiring costly orthonormalization for large-scale matrices, or employ landing methods that rely on careful step siz