Zobrazeno 1 - 10
of 221
pro vyhledávání: '"Xing, Huanlai"'
Attention-based models have been widely used in many areas, such as computer vision and natural language processing. However, relevant applications in time series classification (TSC) have not been explored deeply yet, causing a significant number of
Externí odkaz:
http://arxiv.org/abs/2207.07564
Multi-access edge computing (MEC) and network function virtualization (NFV) are promising technologies to support emerging IoT applications, especially those computation-intensive. In NFV-enabled MEC environment, service function chain (SFC), i.e., a
Externí odkaz:
http://arxiv.org/abs/2205.09925
Autor:
Song, Fuhong, Xing, Huanlai, Wang, Xinhan, Luo, Shouxi, Dai, Penglin, Xiao, Zhiwen, Zhao, Bowen
This paper studies the trajectory control and task offloading (TCTO) problem in an unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where a UAV flies along a planned trajectory to collect computation tasks from smart devices (SDs)
Externí odkaz:
http://arxiv.org/abs/2202.12028
This paper proposes an efficient federated distillation learning system (EFDLS) for multi-task time series classification (TSC). EFDLS consists of a central server and multiple mobile users, where different users may run different TSC tasks. EFDLS ha
Externí odkaz:
http://arxiv.org/abs/2201.00011
Publikováno v:
In Computer Networks December 2024 254
Autor:
Rehman, Amir, Xing, Huanlai, Feng, Li, Hussain, Mehboob, Gulzar, Nighat, Adnan Khan, Muhammad, Hussain, Abid, Saeed, Dhekra
Publikováno v:
In Biomedical Signal Processing and Control March 2024 89
Autor:
Rehman, Amir, Xing, Huanlai, Hussain, Mehboob, Gulzar, Nighat, Khan, Muhammad Adnan, Hussain, Abid, Mahmood, Sajid
Publikováno v:
In Knowledge-Based Systems 25 January 2024 284
Publikováno v:
In Engineering Applications of Artificial Intelligence January 2024 127 Part A
Time series data usually contains local and global patterns. Most of the existing feature networks pay more attention to local features rather than the relationships among them. The latter is, however, also important yet more difficult to explore. To
Externí odkaz:
http://arxiv.org/abs/2011.11829
Time series analysis plays a vital role in various applications, for instance, healthcare, weather prediction, disaster forecast, etc. However, to obtain sufficient shapelets by a feature network is still challenging. To this end, we propose a novel
Externí odkaz:
http://arxiv.org/abs/2008.07707