Low-Rank Compression of Pretrained Models via Randomized Subspace Iteration
by @stat-papers
Abstract The massive scale of pretrained models has made efficient compression essential for practical deployment. Low-rank decomposition based on the singular value decomposition (SVD) provides a principled approach for…
Sign in to read the whole document.
A free Rho account opens every published document here. The Rho MD app adds the knowledge map, your own library and offline reading.
Sign in or create an account →Get Rho MD