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20182022
most citedA Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks

34 citations · 67 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.LG2022

Faith: An Efficient Framework for Transformer Verification on GPUs

Boyuan Feng, Tianqi Tang, Yuke Wang +5

Transformer verification draws increasing attention in machine learning research and industry. It formally verifies the robustness of transformers against adversarial attacks such…

cs.LG2022★ 2 cited

Dynamic N:M Fine-grained Structured Sparse Attention Mechanism

Zhaodong Chen, Yuying Quan, Zheng Qu +3

Transformers are becoming the mainstream solutions for various tasks like NLP and Computer vision. Despite their success, the high complexity of the attention mechanism hinders the…

cs.LG2021★ 12 cited

Transformer Acceleration with Dynamic Sparse Attention

Liu Liu, Zheng Qu, Zhaodong Chen +2

Transformers are the mainstream of NLP applications and are becoming increasingly popular in other domains such as Computer Vision. Despite the improvements in model quality, the e…

cs.LG2020★ 34 cited

A Comprehensive and Modularized Statistical Framework for Gradient Norm Equality in Deep Neural Networks

Zhaodong Chen, Lei Deng, Bangyan Wang +2

In recent years, plenty of metrics have been proposed to identify networks that are free of gradient explosion and vanishing. However, due to the diversity of network components an…

cs.LG2018★ 1 cited

Batch Normalization Sampling

Zhaodong Chen, Lei Deng, Guoqi Li +4

Deep Neural Networks (DNNs) thrive in recent years in which Batch Normalization (BN) plays an indispensable role. However, it has been observed that BN is costly due to the reducti…