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20172026
most citedLow Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time

3 citations · 13 across the 23 of their papers we have counts for

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7 papers · 1 filter

cs.LG2023★ 1 cited

Solving Attention Kernel Regression Problem via Pre-conditioner

Zhao Song, Junze Yin, Lichen Zhang

The attention mechanism is the key to large language models, and the attention matrix serves as an algorithmic and computational bottleneck for such a scheme. In this paper, we def…

cs.LG2023★ 1 cited

Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation

Zhao Song, Mingquan Ye, Junze Yin +1

Weighted low rank approximation is a fundamental problem in numerical linear algebra, and it has many applications in machine learning. Given a matrix $M \in \mathbb{R}^{n \times n…

cs.LG2023★ 3 cited

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time

Yuzhou Gu, Zhao Song, Junze Yin +1

Given a matrix , the low rank matrix completion problem asks us to find a rank- approximation of as for …

cs.LG2022★ 2 cited

Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability

Zhao Song, Yitan Wang, Zheng Yu +1

Sketching is one of the most fundamental tools in large-scale machine learning. It enables runtime and memory saving via randomly compressing the original large problem into lower…

cs.LG2022★ 1 cited

Neural Architecture Search for Inversion

Cheng Zhan, Licheng Zhang, Xin Zhao +2

Over the year, people have been using deep learning to tackle inversion problems, and we see the framework has been applied to build relationship between recording wavefield and ve…

cs.LG2021

Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time

Zhao Song, Lichen Zhang, Ruizhe Zhang

We consider the problem of training a multi-layer over-parametrized neural network to minimize the empirical risk induced by a loss function. In the typical setting of over-paramet…