Outlier detection: Methods, models, and classification
A Boukerche, L Zheng, O Alfandi - ACM Computing Surveys (CSUR), 2020 - dl.acm.org
Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of efficient outlier detection techniques while taking into consideration …
to the design of efficient outlier detection techniques while taking into consideration …
When machine learning meets privacy in 6G: A survey
The rapid-developing Artificial Intelligence (AI) technology, fast-growing network traffic, and
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
emerging intelligent applications (eg, autonomous driving, virtual reality, etc.) urgently …
Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
Task offloading in vehicular edge computing networks: A load-balancing solution
Recently, the rapid advance of vehicular networks has led to the emergence of diverse delay-
sensitive vehicular applications such as automatic driving, auto navigation. Note that …
sensitive vehicular applications such as automatic driving, auto navigation. Note that …
Deep-learning-based millimeter-wave massive MIMO for hybrid precoding
H Huang, Y Song, J Yang, G Gui… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been
regarded to be an emerging solution for the next generation of communications, in which …
regarded to be an emerging solution for the next generation of communications, in which …
UAV-enhanced intelligent offloading for Internet of Things at the edge
With the explosive growth of diverse Internet of Things (IoT) applications, mobile edge
computing (MEC) has been brought to settle the conflict between computation-intensive …
computing (MEC) has been brought to settle the conflict between computation-intensive …
Smart resource allocation for mobile edge computing: A deep reinforcement learning approach
The development of mobile devices with improving communication and perceptual
capabilities has brought about a proliferation of numerous complex and computation …
capabilities has brought about a proliferation of numerous complex and computation …
Computation resource allocation and task assignment optimization in vehicular fog computing: A contract-matching approach
Vehicular fog computing (VFC) has emerged as a promising solution to relieve the overload
on the base station and reduce the processing delay during the peak time. The computation …
on the base station and reduce the processing delay during the peak time. The computation …
Online deep reinforcement learning for computation offloading in blockchain-empowered mobile edge computing
Offloading computation-intensive tasks (eg, blockchain consensus processes and data
processing tasks) to the edge/cloud is a promising solution for blockchain-empowered …
processing tasks) to the edge/cloud is a promising solution for blockchain-empowered …
Partial offloading scheduling and power allocation for mobile edge computing systems
Mobile edge computing (MEC) is a promising technique to enhance computation capacity at
the edge of mobile networks. The joint problem of partial offloading decision, offloading …
the edge of mobile networks. The joint problem of partial offloading decision, offloading …