no code implementations • 7 Mar 2023 • Shuai Wang, Daoan Zhang, JianGuo Zhang, Weiwei Zhang, Rui Li
In this paper, considering the balance of data/model privacy of model owners and user needs, we propose a new setting called Back-Propagated Black-Box Adaptation (BPBA) for users to better train their private models via the guidance of the back-propagated results of a Black-box foundation/source model.
1 code implementation • 26 Nov 2021 • Min Li, Zhengyuan Shi, Zezhong Wang, Weiwei Zhang, Yu Huang, Qiang Xu
The proposed GA-guided XORNets also allows reducing the number of control bits, and the total testing time decreases by 20. 78% on average and up to 47. 09% compared to the existing design without sacrificing test coverage.
no code implementations • 26 Oct 2021 • Mingchao Li, Yerui Chen, Weiwei Zhang, Qiang Chen
Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging modality that allows micron-level resolution to visualize the retinal microvasculature.
no code implementations • 12 Jan 2021 • Mengfei Xu, Shufang Song, Xuxiang Sun, Weiwei Zhang
In order to overcome the limitations of FNN and CNN, the unstructured convolutional neural network (UCNN) is proposed, which aggregates and effectively exploits the features of neighbour nodes through the weight function.
no code implementations • 21 Dec 2020 • Jixuan Wang, Kai Wei, Martin Radfar, Weiwei Zhang, Clement Chung
We propose a novel Transformer encoder-based architecture with syntactical knowledge encoded for intent detection and slot filling.
1 code implementation • 28 Sep 2020 • Wenbo Cao, Weiwei Zhang
Machine learning of partial differential equations from data is a potential breakthrough to solve the lack of physical equations in complex dynamic systems, but because numerical differentiation is ill-posed to noise data, noise has become the biggest obstacle in the application of partial differential equation identification method.
no code implementations • 28 Oct 2019 • Weiwei Zhang, Changsheng chen, Xuechun Wu, Jialin Gao, Di Bao, Jiwei Li, Xi Zhou
In this paper, we propose an adaptive pruning method.
no code implementations • 24 Jul 2019 • Ming Li, Weiwei Zhang, Guang Yang, Chengjia Wang, Heye Zhang, Huafeng Liu, Wei Zheng, Shuo Li
Our method is built as an end-to-end framework for segmentation and classification.
no code implementations • 22 Jul 2019 • Bin-Bin Yang, Weiwei Zhang
Developed from the seminal FCN with an end-to-end learning-based approach and constructed by newly designed dense blocks including a dense fully-connected layer, the proposed FD-FCN is different from other FCN-based methods and leads to an outperformance in the perspective of both efficiency and accuracy.