Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Yu Yingchao"'
Federated learning (FL) has emerged as a promising paradigm for training models on decentralized data while safeguarding data privacy. Most existing FL systems, however, assume that all machine learning models are of the same type, although it become
Externí odkaz:
http://arxiv.org/abs/2406.09680
Federated learning (FL) offers a privacy-preserving approach to machine learning for multiple collaborators without sharing raw data. However, the existence of non-independent and non-identically distributed (non-IID) datasets across different client
Externí odkaz:
http://arxiv.org/abs/2406.09682
Autor:
Yu, Yingchao, Pan, Junxiao, Wu, Honghui, Zhu, Juntao, Zong, Ning, An, Hui, Wang, Changhui, Zuo, Xiaoan, Wei, Cunzheng, Zhang, Fawei, Liu, Shuang, Liu, Jielin, Diao, Huajie, Zhang, Bo, Yu, Qiang, Zhang, Xinyu
Publikováno v:
In Catena June 2024 241
Improving Fake News Detection by Using an Entity-enhanced Framework to Fuse Diverse Multimodal Clues
Autor:
Qi, Peng, Cao, Juan, Li, Xirong, Liu, Huan, Sheng, Qiang, Mi, Xiaoyue, He, Qin, Lv, Yongbiao, Guo, Chenyang, Yu, Yingchao
Recently, fake news with text and images have achieved more effective diffusion than text-only fake news, raising a severe issue of multimodal fake news detection. Current studies on this issue have made significant contributions to developing multim
Externí odkaz:
http://arxiv.org/abs/2108.10509
Publikováno v:
Parasite, Vol 21, p 36 (2014)
Cryptosporidium is one of the most important parasites in poultry, and this pathogen can infect more than 30 avian species. The present study investigated the infection rate of Cryptosporidium among broiler chicken flocks. A total of 385 fecal sample
Externí odkaz:
https://doaj.org/article/49134bc2acb946c29535256d89b08980
Autor:
Levin, Barnaby D. A., Padgett, Elliot, Chen, Chien-Chun, Scott, M. C., Xu, Rui, Theis, Wolfgang, Jiang, Yi, Yang, Yongsoo, Ophus, Colin, Zhang, Haitao, Ha, Don-Hyung, Wang, Deli, Yu, Yingchao, Abruna, Hector D., Robinson, Richard D., Ercius, Peter, Kourkoutis, Lena F., Miao, Jianwei, Muller, David A., Hovden, Robert
Publikováno v:
Scientific Data 3, Article number: 160041 (2016)
Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution an
Externí odkaz:
http://arxiv.org/abs/1606.02938
Autor:
Hovden, Robert, Ercius, Peter, Jiang, Yi, Wang, Deli, Yu, Yingchao, Abruna, Hector D., Elser, Veit, Muller, David A.
To date, high-resolution (< 1 nm) imaging of extended objects in three-dimensions (3D) has not been possible. A restriction known as the Crowther criterion forces a tradeoff between object size and resolution for 3D reconstructions by tomography. Fur
Externí odkaz:
http://arxiv.org/abs/1402.0028
Autor:
Holtz, Megan E., Yu, Yingchao, Gunceler, Deniz, Gao, Jie, Sundararaman, Ravishankar, Schwarz, Kathleen A., Arias, Tomás A., Abruña, Héctor D., Muller, David A.
A major challenge in the development of new battery materials is understanding their fundamental mechanisms of operation and degradation. Their microscopically inhomogeneous nature calls for characterization tools that provide operando and localized
Externí odkaz:
http://arxiv.org/abs/1311.6490
In situ scanning transmission electron microscopy (STEM) through liquids is a promising approach for exploring biological and materials processes. However, options for in situ chemical identification are limited: X-ray analysis is precluded because t
Externí odkaz:
http://arxiv.org/abs/1212.1501
Autor:
Werner, Denis, Burnier, Céline, Yu, Yingchao, Marolf, André R., Wang, Yuanfeng, Massonnet, Geneviève
Publikováno v:
In Science & Justice November 2019 59(6):643-653