A review of recent deep learning approaches in human-centered machine learning
T Kaluarachchi, A Reis, S Nanayakkara - Sensors, 2021 - mdpi.com
After Deep Learning (DL) regained popularity recently, the Artificial Intelligence (AI) or
Machine Learning (ML) field is undergoing rapid growth concerning research and real-world …
Machine Learning (ML) field is undergoing rapid growth concerning research and real-world …
Game theory for multi-access edge computing: Survey, use cases, and future trends
J Moura, D Hutchison - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
Game theory (GT) has been used with significant success to formulate, and either design or
optimize, the operation of many representative communications and networking scenarios …
optimize, the operation of many representative communications and networking scenarios …
Smart cyber–physical systems: toward pervasive intelligence systems
Cyber–physical systems (CPSs) are the next generation of engineering systems, in which
computing, communication and process control technologies are transparently integrated …
computing, communication and process control technologies are transparently integrated …
A dynamic tradeoff data processing framework for delay-sensitive applications in cloud of things systems
The steep rise of Internet of Things (IoT) applications along with the limitations of Cloud
Computing to address all IoT requirements leveraged a new distributed computing paradigm …
Computing to address all IoT requirements leveraged a new distributed computing paradigm …
Application-aware resource allocation and data management for MEC-assisted IoT service providers
S Bolettieri, R Bruno, E Mingozzi - Journal of Network and Computer …, 2021 - Elsevier
To support the growing demand for data-intensive and low-latency IoT applications, Multi-
Access Edge Computing (MEC) is emerging as an effective edge-computing approach …
Access Edge Computing (MEC) is emerging as an effective edge-computing approach …
Hybrid evolutionary scheduling for energy-efficient fog-enhanced internet of things
In recent years, the rapid development of the Internet of Things (IoT) has produced a large
amount of data that needs to be processed in a timely manner. Traditional cloud computing …
amount of data that needs to be processed in a timely manner. Traditional cloud computing …
Joint application admission control and network slicing in virtual sensor networks
We focus on the problem of managing a shared physical wireless sensor network (WSN)
where a single network infrastructure provider leases the physical resources of the networks …
where a single network infrastructure provider leases the physical resources of the networks …
Cost-effective processing for delay-sensitive applications in cloud of things systems
The steep rise of Internet of Things (IoT) applications along with the limitations of Cloud
Computing to address all IoT requirements promotes a new distributed computing paradigm …
Computing to address all IoT requirements promotes a new distributed computing paradigm …
A multi-sensor data fusion technique using data correlations among multiple applications
While wireless sensor networks (WSNs) have been traditionally tasked with single
applications, in recent years we have witnessed the emergence of WSNs that allow the …
applications, in recent years we have witnessed the emergence of WSNs that allow the …
An ensemble random forest algorithm for insurance big data analysis
Z Wu, W Lin, Z Zhang, A Wen… - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
Due to the imbalanced distribution of business data, missing of user features and many
other reasons, directly using big data techniques on realistic business data tends to deviate …
other reasons, directly using big data techniques on realistic business data tends to deviate …