1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2019
Towards Efficient Model Compression via Learned Global Ranking
Ting-Wu Chin, Ruizhou Ding, Cha Zhang +1
Pruning convolutional filters has demonstrated its effectiveness in compressing ConvNets. Prior art in filter pruning requires users to specify a target model complexity (e.g., mod…
cs.CV2018
Layer-compensated Pruning for Resource-constrained Convolutional Neural Networks
Ting-Wu Chin, Cha Zhang, Diana Marculescu
Resource-efficient convolution neural networks enable not only the intelligence on edge devices but also opportunities in system-level optimization such as scheduling. In this work…
cs.CV2017★ 1 cited
Orthogonal and Idempotent Transformations for Learning Deep Neural Networks
Jingdong Wang, Yajie Xing, Kexin Zhang +1
Identity transformations, used as skip-connections in residual networks, directly connect convolutional layers close to the input and those close to the output in deep neural netwo…