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of 76
pro vyhledávání: '"Yu, Chaofan"'
For the two-mode electron pairing, we propose a local stacking force pairing mechanism driven by strong local fluctuations, with two straight pairing orbits where the tying Cooper pairing $C_{-k\downarrow}C_{k\uparrow}e^{ik\cdot r}$ replaces the itin
Externí odkaz:
http://arxiv.org/abs/2409.04317
The distributed (federated) LLM is an important method for co-training the domain-specific LLM using siloed data. However, maliciously stealing model parameters and data from the server or client side has become an urgent problem to be solved. In thi
Externí odkaz:
http://arxiv.org/abs/2401.09796
Publikováno v:
In International Journal of Hydrogen Energy 19 September 2024 83:604-613
Autor:
Wang, Zhuo, Zhang, Jun, Liu, Jiantao, Huang, Jingjing, Zhu, Guorui, Yu, Chaofan, Zhou, Hongtao
Publikováno v:
In Energy Reports June 2024 11:483-497
Autor:
Ma, Junming, Yu, Chaofan, Zhou, Aihui, Wu, Bingzhe, Wu, Xibin, Chen, Xingyu, Chen, Xiangqun, Wang, Lei, Cao, Donggang
We present S3ML, a secure serving system for machine learning inference in this paper. S3ML runs machine learning models in Intel SGX enclaves to protect users' privacy. S3ML designs a secure key management service to construct flexible privacy-prese
Externí odkaz:
http://arxiv.org/abs/2010.06212
Autor:
Law, Andrew, Leung, Chester, Poddar, Rishabh, Popa, Raluca Ada, Shi, Chenyu, Sima, Octavian, Yu, Chaofan, Zhang, Xingmeng, Zheng, Wenting
In recent years, gradient boosted decision tree learning has proven to be an effective method of training robust models. Moreover, collaborative learning among multiple parties has the potential to greatly benefit all parties involved, but organizati
Externí odkaz:
http://arxiv.org/abs/2010.02524
Autor:
Fang, Wenjing, Zhao, Derun, Tan, Jin, Chen, Chaochao, Yu, Chaofan, Wang, Li, Wang, Lei, Zhou, Jun, Zhang, Benyu
Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of privacy regulations come into force. Under such situation, Federated Learning (FL) appears to facilitate privacy-preserving joint modeling among m
Externí odkaz:
http://arxiv.org/abs/2005.08479
Publikováno v:
In Knowledge-Based Systems 3 December 2023 281
Akademický článek
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Publikováno v:
In Applied Energy 15 January 2023 330 Part B