2025
Perturbation Bounds for Low-Rank Inverse Approximations under Noise
NeurIPS 2025poster
Low-rank pseudoinverses are widely used to approximate matrix inverses in scalable machine learning, optimization, and scientific computing. However, real-world matrices are often observed with noise, arising from sampling, sketching, and quantization. The spectral-norm robustness of low-rank invers…