3 citations · 3 across the 4 of their papers we have counts for
4 papers
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network
Xuan Shen, Yaohua Wang, Ming Lin +4
The rapid advances in Vision Transformer (ViT) refresh the state-of-the-art performances in various vision tasks, overshadowing the conventional CNN-based models. This ignites a fe…
Survey: Exploiting Data Redundancy for Optimization of Deep Learning
Jou-An Chen, Wei Niu, Bin Ren +2
Data redundancy is ubiquitous in the inputs and intermediate results of Deep Neural Networks (DNN). It offers many significant opportunities for improving DNN performance and effic…
Quantum Neural Network Compression
Zhirui Hu, Peiyan Dong, Zhepeng Wang +3
Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there are growing interest…
CoCoPIE XGen: A Full-Stack AI-Oriented Optimizing Framework
Xiaofeng Li, Bin Ren, Xipeng Shen +1
There is a growing demand for shifting the delivery of AI capability from data centers on the cloud to edge or end devices, exemplified by the fast emerging real-time AI-based apps…