v0.5.0

What's Changed

• refactor: threshold refactorized; threshold tests added by @massimofedrigo in #7

Full Changelog: v0.4.0...v0.5.0

v0.4.0

What's Changed

• Feat/scikit learn compatibility by @massimofedrigo in #5
• Feat/randomized pca by @massimofedrigo in #6

Full Changelog: v0.3.0...v0.4.0

v0.3.0

What's Changed

• fix: examples fixed and updated by @massimofedrigo in #3
• Feat/sparse matrix support by @massimofedrigo in #4

Full Changelog: v0.2.0...v0.3.0

v0.2.0

What's Changed

• Feat/power iterations by @massimofedrigo in #1
• Feat/oversampling by @massimofedrigo in #2

New Contributors

• @massimofedrigo made their first contribution in #1

Full Changelog: v0.1.0...v0.2.0

v0.1.0 - Initial Release

🚀 Initial Release (v0.1.0)

• Core Algorithm: Fast implementation of Randomized SVD compatible with standard NumPy arrays.
• Smart Optimization: Automatic dispatching for Tall-and-Skinny vs Short-and-Fat matrices to minimize memory usage.
• Denoising: Included implementation of the Gavish-Donoho optimal threshold for rank selection.
• Zero Bloat: Lightweight package with numpy as the only core dependency.