4 citations · 9 across the 3 of their papers we have counts for
6 papers
EAPruning: Evolutionary Pruning for Vision Transformers and CNNs
Qingyuan Li, Bo Zhang, Xiangxiang Chu
Structured pruning greatly eases the deployment of large neural networks in resource-constrained environments. However, current methods either involve strong domain expertise, requ…
AutoKWS: Keyword Spotting with Differentiable Architecture Search
Bo Zhang, Wenfeng Li, Qingyuan Li +3
Smart audio devices are gated by an always-on lightweight keyword spotting program to reduce power consumption. It is however challenging to design models that have both high accur…
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators
Xiangxiang Chu, Xiaoxing Wang, Bo Zhang +3
Despite the fast development of differentiable architecture search (DARTS), it suffers from long-standing performance instability, which extremely limits its application. Existing…
MoGA: Searching Beyond MobileNetV3
Xiangxiang Chu, Bo Zhang, Ruijun Xu
The evolution of MobileNets has laid a solid foundation for neural network applications on mobile end. With the latest MobileNetV3, neural architecture search again claimed its sup…
A Matrix-in-matrix Neural Network for Image Super Resolution
Hailong Ma, Xiangxiang Chu, Bo Zhang +1
In recent years, deep learning methods have achieved impressive results with higher peak signal-to-noise ratio in single image super-resolution (SISR) tasks by utilizing deeper lay…
Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
Xiangxiang Chu, Bo Zhang, Hailong Ma +2
Deep convolutional neural networks demonstrate impressive results in the super-resolution domain. A series of studies concentrate on improving peak signal noise ratio (PSNR) by usi…