Zobrazeno 1 - 10
of 6 791
pro vyhledávání: '"Shihai An"'
Autor:
Dongmei Hu, Sihao Deng, Ying Sun, Kewen Shi, Xiuliang Yuan, Shihai An, Lunhua He, Jie Chen, Yuanhua Xia, Cong Wang
Publikováno v:
Journal of Materiomics, Vol 10, Iss 2, Pp 456-462 (2024)
Magnetic materials with non-collinear spin orderings provide an outstanding platform to probe spintronic phenomena owing to their strong spin-orbit coupling (SOC) and unique Berry phase. It is thus important to obtain a non-collinear antiferromagneti
Externí odkaz:
https://doaj.org/article/b58a0311ae574d26908e4a48ce2fc5a3
Autor:
Zhang, Xueying, Zhang, Bin, Wei, Shihai, Li, Hao, Liao, Jinyu, Zhou, Tao, Deng, Guangwei, Wang, You, Song, Haizhi, You, Lixing, Fan, Boyu, Fan, Yunru, Chen, Feng, Guo, Guangcan, Zhou, Qiang
Light-matter interface is an important building block for long-distance quantum networks. Towards a scalable quantum network with high-rate quantum information processing, it requires to develop integrated light-matter interfaces with broadband and m
Externí odkaz:
http://arxiv.org/abs/2410.18516
Autor:
Tian, Bing, Liu, Haikun, Tang, Yuhang, Xiao, Shihai, Duan, Zhuohui, Liao, Xiaofei, Zhang, Xuecang, Zhu, Junhua, Zhang, Yu
Approximate nearest neighbor search (ANNS) has emerged as a crucial component of database and AI infrastructure. Ever-increasing vector datasets pose significant challenges in terms of performance, cost, and accuracy for ANNS services. None of modern
Externí odkaz:
http://arxiv.org/abs/2409.16576
In this note, we comprehensively characterize the proximal operator of the $\ell_{1,q}$-norm with $0\!<\!q\!<\!1$ by exploiting the well-known proximal operator of the $\ell_q$-norm on the real line. In particular, much more explicit characterization
Externí odkaz:
http://arxiv.org/abs/2409.14156
Reference frame independent quantum key distribution (RFI-QKD) has gained widespread attention due to the unique advantage for practical application, as it circumvents the need for active reference frame alignment within the system. However, in compa
Externí odkaz:
http://arxiv.org/abs/2405.16518
Autor:
Qin, Zhi, He, Zhoubo, Cao, Zhe, Chen, Tao, Deng, Zhi, Duan, Limin, Guo, Dong, Hu, Rongjiang, Kong, Jie, Liu, Canwen, Ma, Peng, Wei, Xianglun, Wen, Shihai, Wen, Xiangjie, Yan, Junwei, Yang, Herun, Yang, Zuoqiao, Yu, Yuhong, Xiao, Zhigang
The half-size prototype of the multi wire drift chamber (MWDC) for the cooling storage ring (CSR) external-target experiment (CEE) was assembled and tested in 350 MeV/u Kr+Fe reactions on the heavy ion research facility in Lanzhou (HIRFL). The protot
Externí odkaz:
http://arxiv.org/abs/2406.12878
Publikováno v:
Optics Express, Vol.32, No.13/17, 22460 (2024)
Reference-frame-independent (RFI) quantum key distribution (QKD) presents promising advantages, especially for mobile-platform-based implementations, as it eliminates the need for active reference frame calibration. While RFI-QKD has been explored in
Externí odkaz:
http://arxiv.org/abs/2403.10294
Autor:
Xiuliang Yuan, Ying Sun, Huaiming Guo, Kewen Shi, Ping Song, Huimin Han, Jin Cui, Shihai An, Rongjin Huang, Laifeng Li, Cong Wang
Publikováno v:
Materials & Design, Vol 203, Iss , Pp 109591- (2021)
The negative thermal expansion (NTE) or nearly zero thermal expansion (NZTE) behaviors have been found in some magnetic metallic compounds with great application prospects. However, it is a big challenge for applications that the responding temperatu
Externí odkaz:
https://doaj.org/article/cfba40ba186c449198dca108299d23bb
Autor:
Liu, Ping, Wei, Haichao, Hou, Xiaochen, Shen, Jianqiang, He, Shihai, Shen, Kay Qianqi, Chen, Zhujun, Borisyuk, Fedor, Hewlett, Daniel, Wu, Liang, Veeraraghavan, Srikant, Tsun, Alex, Jiang, Chengming, Zhang, Wenjing
We present LinkSAGE, an innovative framework that integrates Graph Neural Networks (GNNs) into large-scale personalized job matching systems, designed to address the complex dynamics of LinkedIns extensive professional network. Our approach capitaliz
Externí odkaz:
http://arxiv.org/abs/2402.13430
Autor:
Borisyuk, Fedor, He, Shihai, Ouyang, Yunbo, Ramezani, Morteza, Du, Peng, Hou, Xiaochen, Jiang, Chengming, Pasumarthy, Nitin, Bannur, Priya, Tiwana, Birjodh, Liu, Ping, Dangi, Siddharth, Sun, Daqi, Pei, Zhoutao, Shi, Xiao, Zhu, Sirou, Shen, Qianqi, Lee, Kuang-Hsuan, Stein, David, Li, Baolei, Wei, Haichao, Ghoting, Amol, Ghosh, Souvik
In this paper, we present LiGNN, a deployed large-scale Graph Neural Networks (GNNs) Framework. We share our insight on developing and deployment of GNNs at large scale at LinkedIn. We present a set of algorithmic improvements to the quality of GNN r
Externí odkaz:
http://arxiv.org/abs/2402.11139