Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Zhou, Huilin"'
The AI model has surpassed human players in the game of Go, and it is widely believed that the AI model has encoded new knowledge about the Go game beyond human players. In this way, explaining the knowledge encoded by the AI model and using it to te
Externí odkaz:
http://arxiv.org/abs/2310.09838
Autor:
Zhou, Huilin, Zhang, Hao, Deng, Huiqi, Liu, Dongrui, Shen, Wen, Chan, Shih-Han, Zhang, Quanshi
This paper explains the generalization power of a deep neural network (DNN) from the perspective of interactions. Although there is no universally accepted definition of the concepts encoded by a DNN, the sparsity of interactions in a DNN has been pr
Externí odkaz:
http://arxiv.org/abs/2302.13091
Publikováno v:
In Food Chemistry 30 October 2024 456
Autor:
Fu, Zhenyu, Dong, Zhenyou, Wang, Qiuke, Zhou, Huilin, Xia, Sihang, Zhou, Xueqing, Shen, Longxiang, Chen, Wenqian, Shi, Wenyan
Publikováno v:
In Chemical Engineering Journal 1 October 2024 497
Autor:
Fu, Zhenyu, Ye, Kai, Dong, Zhenyou, Li, Suyun, Zhou, Huilin, Xia, Sihang, Shen, Longxiang, Shi, Wenyan
Publikováno v:
In Journal of Environmental Chemical Engineering October 2024 12(5)
Autor:
Zhang, Die, Zhou, Huilin, Zhang, Hao, Bao, Xiaoyi, Huo, Da, Chen, Ruizhao, Cheng, Xu, Wu, Mengyue, Zhang, Quanshi
This paper proposes a method to disentangle and quantify interactions among words that are encoded inside a DNN for natural language processing. We construct a tree to encode salient interactions extracted by the DNN. Six metrics are proposed to anal
Externí odkaz:
http://arxiv.org/abs/2007.04298
Cognitive radio is a promising technology to improve spectral efficiency. However, the secure performance of a secondary network achieved by using physical layer security techniques is limited by its transmit power and channel fading. In order to tac
Externí odkaz:
http://arxiv.org/abs/2005.03091
Electromagnetic inverse scattering problems (ISPs) aim to retrieve permittivities of dielectric scatterers from the scattering measurement. It is often highly nonlinear, caus-ing the problem to be very difficult to solve. To alleviate the issue, this
Externí odkaz:
http://arxiv.org/abs/2003.01465
Autor:
Ma, Yehao, Ye, Sijia, Zhao, Dazheng, Liu, Xiaoguang, Cao, Ling, Zhou, Huilin, Zuo, Guokun, Shi, Changcheng
Publikováno v:
In Medical Engineering and Physics July 2023 117
This paper proposes a generic method to learn interpretable convolutional filters in a deep convolutional neural network (CNN) for object classification, where each interpretable filter encodes features of a specific object part. Our method does not
Externí odkaz:
http://arxiv.org/abs/1901.02413