3 citations · 5 across the 2 of their papers we have counts for
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cs.LG2023★ 3 cited
What can a Single Attention Layer Learn? A Study Through the Random Features Lens
Hengyu Fu, Tianyu Guo, Yu Bai +1
Attention layers -- which map a sequence of inputs to a sequence of outputs -- are core building blocks of the Transformer architecture which has achieved significant breakthroughs…
cs.LG2020★ 2 cited
On Positive-Unlabeled Classification in GAN
Tianyu Guo, Chang Xu, Jiajun Huang +4
This paper defines a positive and unlabeled classification problem for standard GANs, which then leads to a novel technique to stabilize the training of the discriminator in GANs.…
cs.LG2018
Robust Student Network Learning
Tianyu Guo, Chang Xu, Shiyi He +3
Deep neural networks bring in impressive accuracy in various applications, but the success often relies on the heavy network architecture. Taking well-trained heavy networks as tea…