Zobrazeno 1 - 10
of 1 251
pro vyhledávání: '"Mei, Hao"'
Autor:
Chen, Zixuan, Liu, Xuandong, Li, Minglin, Hu, Yinfan, Mei, Hao, Xing, Huifeng, Wang, Hao, Shi, Wanxin, Liu, Sen, Xu, Yang
Parameter Server (PS) and Ring-AllReduce (RAR) are two widely utilized synchronization architectures in multi-worker Deep Learning (DL), also referred to as Distributed Deep Learning (DDL). However, PS encounters challenges with the ``incast'' issue,
Externí odkaz:
http://arxiv.org/abs/2407.19721
Autor:
Lin, Yilu, Bailey, James E, Surbhi, Satya, Shuvo, Sohul A, Jackson, Christopher D, Chen, Ming, Price-Haywood, Eboni G, Mann, Joshua, Fort, Daniel, Burton, Jeffrey, Sandlin, Ramona, Castillo, Alexandra, Mei, Hao, Smith, Patti, Leak, Cardella, Le, Phi, Monnette, Alisha M, Shi, Lizheng
Publikováno v:
JMIR Research Protocols, Vol 9, Iss 9, p e20788 (2020)
BackgroundObesity affects nearly half of adults in the United States and is contributing substantially to a pandemic of obesity-associated chronic conditions such as type 2 diabetes, hypertension, and arthritis. The obesity-associated chronic conditi
Externí odkaz:
https://doaj.org/article/607cb307c287482fb1f39ee1d7fcc8bc
Traffic prediction is a crucial topic because of its broad scope of applications in the transportation domain. Recently, various studies have achieved promising results. However, most studies assume the prediction locations have complete or at least
Externí odkaz:
http://arxiv.org/abs/2309.06800
Autor:
MEI Hao, SHANG Yong, CHANG Keke, YU Haiyuan, RU Yi, ZHAO Wenyue, ZHAO Haigen, WANG Wenwen, PEI Yanling, LI Shusuo, GONG Shengkai
Publikováno v:
Journal of Aeronautical Materials, Vol 44, Iss 5, Pp 86-104 (2024)
With the global energy transition and increasing environmental requirements，hydrogen-mixed gas turbines as a high-efficiency and low-emission energy conversion equipment has been widely concerned. This paper reviews the development status of hydrog
Externí odkaz:
https://doaj.org/article/306107d3dde54dc9bc2586222ab77052
Autor:
Yang Li Li, Qi Qi Lu, Wen Wen Zheng, Zhao Yu Zhang, Jin Yi Wu, Mei Hao Wei, Xin Zhuo Zhang, Ruo Dan Liu, Zhong Quan Wang, Jing Cui
Publikováno v:
Veterinary Research, Vol 55, Iss 1, Pp 1-19 (2024)
Abstract Long-chain fatty acid transport protein 1 (FATP1) is a member of the fatty acid transporter family. It facilitates transmembrane transport of fatty acids and participates in lipid metabolism. Lipids are essential components of the cell and o
Externí odkaz:
https://doaj.org/article/89239a4455384d849d01802d532d3abd
Numerous solutions are proposed for the Traffic Signal Control (TSC) tasks aiming to provide efficient transportation and mitigate congestion waste. In recent, promising results have been attained by Reinforcement Learning (RL) methods through trial
Externí odkaz:
http://arxiv.org/abs/2308.14284
Traffic signal control (TSC) is a complex and important task that affects the daily lives of millions of people. Reinforcement Learning (RL) has shown promising results in optimizing traffic signal control, but current RL-based TSC methods are mainly
Externí odkaz:
http://arxiv.org/abs/2307.12388
Graph regression is a fundamental task that has gained significant attention in various graph learning tasks. However, the inference process is often not easily interpretable. Current explanation techniques are limited to understanding Graph Neural N
Externí odkaz:
http://arxiv.org/abs/2307.07840
The emergence of reinforcement learning (RL) methods in traffic signal control tasks has achieved better performance than conventional rule-based approaches. Most RL approaches require the observation of the environment for the agent to decide which
Externí odkaz:
http://arxiv.org/abs/2304.10722
Autor:
Raut, Mathbar, Mei, Dongming, Bhattarai, Sanjay, Panth, Rajendra, Kooi, Kyler, Mei, Hao, Wang, Guojian
This study investigates new technology for enhancing the sensitivity of low-mass dark matter detection by analyzing charge transport in a p-type germanium detector at 5.2 K. To achieve low-threshold detectors, precise calculations of the binding ener
Externí odkaz:
http://arxiv.org/abs/2303.16807