Hanqin Cai

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Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching

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

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cs.LG2025★ 1 cited

Deeply Learned Robust Matrix Completion for Large-scale Low-rank Data Recovery

HanQin Cai, Chandra Kundu, Jialin Liu +1

Robust matrix completion (RMC) is a widely used machine learning tool that simultaneously tackles two critical issues in low-rank data analysis: missing data entries and extreme ou…

cs.LG2024★ 2 cited

S $^{3}$ Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching

Xue Wang, Tian Zhou, Jianqing Zhu +6

Attention based models have achieved many remarkable breakthroughs in numerous applications. However, the quadratic complexity of Attention makes the vanilla Attention based models…

Deeply Learned Robust Matrix Completion for Large-scale Low-rank Data Recovery

S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching

S $^{3}$ Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching