3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
LPViT: Low-Power Semi-structured Pruning for Vision Transformers
Kaixin Xu, Zhe Wang, Chunyun Chen +7
Vision transformers have emerged as a promising alternative to convolutional neural networks for various image analysis tasks, offering comparable or superior performance. However,…
cs.LG2024★ 1 cited
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Xue Geng, Zhe Wang, Chunyun Chen +10
Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI) tasks. However, deploying them brings significant challenges due to the huge cost of memory,…
cs.LG2022★ 3 cited
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning
Manas Gupta, Efe Camci, Vishandi Rudy Keneta +5
Pruning neural networks has become popular in the last decade when it was shown that a large number of weights can be safely removed from modern neural networks without compromisin…