10 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.DC2025
NM-SpMM: Accelerating Matrix Multiplication Using N:M Sparsity with GPGPU
Cong Ma, Du Wu, Zhelang Deng +11
Deep learning demonstrates effectiveness across a wide range of tasks. However, the dense and over-parameterized nature of these models results in significant resource consumption…
cs.LG2023★ 10 cited
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing
Xingyu Xu, Yandi Shen, Yuejie Chi +1
We propose $\textsf{ScaledGD($λ$)}$, a preconditioned gradient descent method to tackle the low-rank matrix sensing problem when the true rank is unknown, and when the matrix is po…