Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Zhao, Haimeng"'
Autor:
Zhao, Haimeng, Deng, Dong-Ling
Quantum computing holds the unparalleled potentials to enhance, speed up or innovate machine learning. However, an unambiguous demonstration of quantum learning advantage has not been achieved so far. Here, we rigorously establish a noise-robust, unc
Externí odkaz:
http://arxiv.org/abs/2410.03094
Autor:
Zhao, Haimeng, Lewis, Laura, Kannan, Ishaan, Quek, Yihui, Huang, Hsin-Yuan, Caro, Matthias C.
While quantum state tomography is notoriously hard, most states hold little interest to practically-minded tomographers. Given that states and unitaries appearing in Nature are of bounded gate complexity, it is natural to ask if efficient learning be
Externí odkaz:
http://arxiv.org/abs/2310.19882
Publikováno v:
Quantum 8, 1358 (2024)
Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments focusing main
Externí odkaz:
http://arxiv.org/abs/2307.01840
Autor:
Zhao, Haimeng
Publikováno v:
Quantum Machine Intelligence 5, 3 (2023)
Federated learning refers to the task of machine learning based on decentralized data from multiple clients with secured data privacy. Recent studies show that quantum algorithms can be exploited to boost its performance. However, when the clients' d
Externí odkaz:
http://arxiv.org/abs/2209.00768
Cybersecurity breaches are the common anomalies for distributed cyber-physical systems (CPS). However, the cyber security breach classification is still a difficult problem, even using cutting-edge artificial intelligence (AI) approaches. In this pap
Externí odkaz:
http://arxiv.org/abs/2209.00170
Autor:
Zhao, Haimeng, Zhu, Wei
Publikováno v:
The Astronomical Journal, 164, 192 (2022)
The modeling of binary microlensing light curves via the standard sampling-based method can be challenging, because of the time-consuming light-curve computation and the pathological likelihood landscape in the high-dimensional parameter space. In th
Externí odkaz:
http://arxiv.org/abs/2206.08199
Autor:
Zhao, Haimeng, Liao, Peiyuan
We introduce ADMM-pruned Compressive AutoEncoder (CAE-ADMM) that uses Alternative Direction Method of Multipliers (ADMM) to optimize the trade-off between distortion and efficiency of lossy image compression. Specifically, ADMM in our method is to pr
Externí odkaz:
http://arxiv.org/abs/1901.07196
Autor:
Wang, Qingpeng, Chen, Wei, Tang, Hongzhao, Pan, Xubin, Zhao, Haimeng, Yang, Bin, Zhang, Honggeng, Gu, Wenzhu
Publikováno v:
In Science of the Total Environment 10 May 2023 872
Autor:
Zhao, Haimeng1,2 (AUTHOR) zhaohaimeng@guat.edu.cn, Yin, Xiaojian1,3 (AUTHOR) yinxiaojian@stu.gxun.edu.cn, Li, Anran1,4 (AUTHOR) 2221002019@cnu.edu.cn, Zhang, Huimin1,4 (AUTHOR) 2211002008@cnu.edu.cn, Pan, Danqing1 (AUTHOR) pandq@guat.edu.cn, Pan, Jinjin1 (AUTHOR) jphan@guat.edu.cn, Zhu, Jianfang1 (AUTHOR) ghzjf@guat.edu.cn, Wang, Mingchun1 (AUTHOR) wangmingchun@guat.edu.cn, Sun, Shanlin1,3 (AUTHOR) sunsl@guat.edu.cn, Wang, Qiang5 (AUTHOR) qwang@tjnu.edu.cn
Publikováno v:
Remote Sensing. Dec2023, Vol. 15 Issue 23, p5526. 22p.
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