no code implementations • 28 Nov 2021 • Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, ChenChen Liu, Zhi Tian, Xiang Chen
Federated learning learns from scattered data by fusing collaborative models from local nodes.
no code implementations • 15 Aug 2020 • Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, ChenChen Liu, Zhi Tian, Xiang Chen
Specifically, we design a feature-oriented regulation method ({$\Psi$-Net}) to ensure explicit feature information allocation in different neural network structures.
no code implementations • 10 May 2019 • Fuxun Yu, Zhuwei Qin, Chenchen Liu, Liang Zhao, Yanzhi Wang, Xiang Chen
Recently, adversarial deception becomes one of the most considerable threats to deep neural networks.
no code implementations • ICLR 2019 • Zhuwei Qin, Fuxun Yu, ChenChen Liu, Xiang Chen
As significant redundancies inevitably present in such a structure, many works have been proposed to prune the convolutional filters for computation cost reduction.
no code implementations • NIPS Workshop CDNNRIA 2018 • Zhuwei Qin, Fuxun Yu, ChenChen Liu, Xiang Chen
We find that the filter magnitude based method fails to eliminate the filters with repetitive functionality.
no code implementations • NIPS Workshop CDNNRIA 2018 • Fuxun Yu, Zhuwei Qin, Xiang Chen
Neural network compression and acceleration are widely demanded currently due to the resource constraints on most deployment targets.
no code implementations • ICLR 2019 • Zhuwei Qin, Fuxun Yu, ChenChen Liu, Xiang Chen
As significant redundancies inevitably present in such a structure, many works have been proposed to prune the convolutional filters for computation cost reduction.
1 code implementation • 30 Apr 2018 • Zhuwei Qin, Fuxun Yu, ChenChen Liu, Xiang Chen
Nowadays, the Convolutional Neural Networks (CNNs) have achieved impressive performance on many computer vision related tasks, such as object detection, image recognition, image retrieval, etc.