3 papers
math.NA2026
Improving Sketching Algorithms for Low-Rank Matrix Approximation via Sketch-Power Iterations
Chao Chang, Yuning Yang
Power iteration can improve the accuracy of randomized SVD, but requires multiple data passes, making it impractical in streaming or memory-constrained settings. We introduce a lig…
cs.CV2026
DeepInv: A Novel Self-supervised Learning Approach for Fast and Accurate Diffusion Inversion
Ziyue Zhang, Luxi Lin, Xiaolin Hu +4
Diffusion inversion is a task of recovering the noise of an image in a diffusion model, which is vital for controllable diffusion image editing. At present, diffusion inversion sti…
math.NA2024
Randomized Large-Scale Quaternion Matrix Approximation: Practical Rangefinders and One-Pass Algorithm
Chao Chang, Yuning Yang
Recently, randomized algorithms for low-rank approximation of quaternion matrices have received increasing attention. However, for large-scale problems, existing quaternion orthono…