1 citations · 1 across the 3 of their papers we have counts for
5 papers
How Sparse Attention Approximates Exact Attention? Your Attention is Naturally -Sparse
Yichuan Deng, Zhao Song, Jing Xiong +1
Sparse Attention is a technique that approximates standard attention computation with sub-quadratic complexity. This is achieved by selectively ignoring smaller entries in the atte…
Enhancing Stochastic Gradient Descent: A Unified Framework and Novel Acceleration Methods for Faster Convergence
Yichuan Deng, Zhao Song, Chiwun Yang
Based on SGD, previous works have proposed many algorithms that have improved convergence speed and generalization in stochastic optimization, such as SGDm, AdaGrad, Adam, etc. How…
Image change detection with only a few samples
Ke Liu, Zhaoyi Song, Haoyue Bai
This paper considers image change detection with only a small number of samples, which is a significant problem in terms of a few annotations available. A major impediment of image…
Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights
Yichuan Deng, Zhao Song, Shenghao Xie +1
In the realm of deep learning, transformers have emerged as a dominant architecture, particularly in natural language processing tasks. However, with their widespread adoption, con…
Why Softmax Attention Outperforms Linear Attention
Yichuan Deng, Zhao Song, Kaijun Yuan +1
Large transformer models have achieved state-of-the-art results in numerous natural language processing tasks. Among the pivotal components of the transformer architecture, the att…