Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Ye Xiaozhou"'
Publikováno v:
Frontiers in Physics, Vol 11 (2023)
Satellite signal threat is an important kind of satellite signal anomaly, which will lead to ranging biases of user receiver. BOC modulation is used more and more widely in the field of satellite navigation system. In the existing literature, there i
Externí odkaz:
https://doaj.org/article/e566d4c84f464c01938aa076b80f8f87
Autor:
Ye, Xiaozhou, Wang, Kevin I-Kai
Human Activity Recognition (HAR) plays a crucial role in various applications such as human-computer interaction and healthcare monitoring. However, challenges persist in HAR models due to the data distribution differences between training and real-w
Externí odkaz:
http://arxiv.org/abs/2408.03353
Human Activity Recognition (HAR) is a cornerstone of ubiquitous computing, with promising applications in diverse fields such as health monitoring and ambient assisted living. Despite significant advancements, sensor-based HAR methods often operate u
Externí odkaz:
http://arxiv.org/abs/2403.15424
Autor:
Ye, Xiaozhou, Wang, Kevin I-Kai
Current research on human activity recognition (HAR) mainly assumes that training and testing data are drawn from the same distribution to achieve a generalised model, which means all the data are considered to be independent and identically distribu
Externí odkaz:
http://arxiv.org/abs/2403.15423
Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing, analysing behaviours through multi-dimensional observations. Despite research progress, HAR confronts challenges, particularly in data distribution assumptions. Most st
Externí odkaz:
http://arxiv.org/abs/2403.15422
Autor:
Ye, Xiaozhou, Wang, Kevin I-Kai
In Human Activity Recognition (HAR), a predominant assumption is that the data utilized for training and evaluation purposes are drawn from the same distribution. It is also assumed that all data samples are independent and identically distributed ($
Externí odkaz:
http://arxiv.org/abs/2403.17958
Autor:
Ye, Xiaozhou, Wang, Kevin I-Kai
In human activity recognition (HAR), the assumption that training and testing data are independent and identically distributed (i.i.d.) often fails, particularly in cross-user scenarios where data distributions vary significantly. This discrepancy hi
Externí odkaz:
http://arxiv.org/abs/2403.14682
Autor:
Kong, Rui, Li, Yuanchun, Feng, Qingtian, Wang, Weijun, Ye, Xiaozhou, Ouyang, Ye, Kong, Linghe, Liu, Yunxin
Mixture of experts (MoE) is a popular technique to improve capacity of Large Language Models (LLMs) with conditionally-activated parallel experts. However, serving MoE models on memory-constrained devices is challenging due to the large parameter siz
Externí odkaz:
http://arxiv.org/abs/2308.15030
Autor:
Ouyang, Ye, Zhang, Yaqin, Ye, Xiaozhou, Liu, Yunxin, Song, Yong, Liu, Yang, Bian, Sen, Liu, Zhiyong
In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future worl
Externí odkaz:
http://arxiv.org/abs/2307.11449
Autor:
Ouyang, Ye, Zhang, Yaqin, Ye, Xiaozhou, Liu, Yunxin, Wang, Xidong, Sun, Jie, Liu, Yang, Wang, Shoufeng, Bian, Sen, Li, Yun
6G is the next-generation intelligent and integrated digital information infrastructure, characterized by ubiquitous interconnection, native intelligence, multi-dimensional perception, global coverage, green and low-carbon, native network security, e
Externí odkaz:
http://arxiv.org/abs/2307.09045