Search Results for author: Weiwei Zhang

Found 9 papers, 2 papers with code

Bootstrap The Original Latent: Learning a Private Model from a Black-box Model

no code implementations7 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.

Testability-Aware Low Power Controller Design with Evolutionary Learning

1 code implementation26 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.

Image Magnification Network for Vessel Segmentation in OCTA Images

no code implementations26 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.

Retinal Vessel Segmentation

UCNN: A Convolutional Strategy on Unstructured Mesh

no code implementations12 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.

Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling

no code implementations21 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.

Intent Detection Multi-Task Learning +2

Machine Learning of Partial Differential Equations from Noise Data

1 code implementation28 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.

BIG-bench Machine Learning

FD-FCN: 3D Fully Dense and Fully Convolutional Network for Semantic Segmentation of Brain Anatomy

no code implementations22 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.

Anatomy Semantic Segmentation

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