no code implementations • 28 Dec 2023 • Cheng-En Wu, Azadeh Davoodi, Yu Hen Hu
This paper presents a novel approach to network pruning, targeting block pruning in deep neural networks for edge computing environments.
1 code implementation • 4 Dec 2020 • Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee
If the function is incompletely-specified, the implementation has to be true only on the care set.
no code implementations • 8 Aug 2019 • Boyu Zhang, Azadeh Davoodi, Yu Hen Hu
The deployment of Convolutional Neural Networks (CNNs) on resource constrained platforms such as mobile devices and embedded systems has been greatly hindered by their high implementation cost, and thus motivated a lot research interest in compressing and accelerating trained CNN models.
no code implementations • 9 Nov 2018 • Wei Zeng, Azadeh Davoodi, Yu Hen Hu
Design rule check is a critical step in the physical design of integrated circuits to ensure manufacturability.
no code implementations • 31 Oct 2018 • Boyu Zhang, Azadeh Davoodi, Yu-Hen Hu
Since the customized dataset is in general very small, the cost of training LE and GN would be much lower than that of re-training of GE.