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Important complexity reduction of random forest in multi-classification problem
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Algorithm complexity in machine learning problems has been a real concern especially with large-scaled systems. By increasing data dimensionality, a particular emphasis is placed on designing computationally efficient ...
Green data center networks: A holistic survey and design guidelines
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Data Center Networks (DCNs) are attracting immense interest from the industry, research and academia to keep pace with the increase of Internet services demands. One of the major concerns that draws the attention of ...
Machine learning screening of COVID-19 patients based on X-ray images for unbalanced classes
(
Hamad bin Khalifa University Press (HBKU Press)
, 2021 , Article)
Background: COVID-19 is a pandemic that had already infected more than forty-six million people and caused more than a million deaths by 1st of November 2020. The virus pandemic appears to have had a catastrophic effect ...
CODE: Computation Offloading in D2D-Edge System for Video Streaming
(
IEEE
, 2022 , Article)
Video traffic over the Internet is increasing rapidly, reaching up to 82% of the total Internet traffic by 2022. This enormous growth of video traffic which also include immersive video content (augmented reality ...
Federated Learning in NOMA Networks: Convergence, Energy and Fairness-Based Design
(
IEEE
, 2022 , Conference Paper)
Federated Learning (FL) is a collaborative machine learning (ML) approach, where different nodes in a network contribute to learning the model parameters. In addition, FL provides several attractive features such as data ...
Federated Learning for UAV Swarms under Class Imbalance and Power Consumption Constraints
(
IEEE
, 2021 , Conference Paper)
The usage of unmanned aerial vehicles (UAVs) in civil and military applications continues to increase due to the numerous advantages that they provide over conventional approaches. Despite the abundance of such advantages, ...
Secure Medical Data Sharing for Healthcare System
(
IEEE
, 2022 , Conference Paper)
A new generation of advanced information technologies are used nowadays by healthcare systems to provide access to affordable and high-quality healthcare services. However, such services, generally require a large amount ...
Cooperative Machine Learning Techniques for Cloud Intrusion Detection
(
IEEE
, 2021 , Conference Paper)
Cloud computing is attracting a lot of attention in the past few years. Although, even with its wide acceptance, cloud security is still one of the most essential concerns of cloud computing. Many systems have been proposed ...
Data Augmentation for Intrusion Detection and Classification in Cloud Networks
(
IEEE
, 2021 , Conference Paper)
Cloud computing is a paradigm that provides multiple services over the internet with high flexibility in a cost-effective way. However, the growth of cloud-based services comes with major security issues. Recently, machine ...
Joint learning and optimization for Federated Learning in NOMA-based networks
(
Elsevier
, 2023 , Article)
Over the past decade, the usage of machine learning (ML) techniques have increased substantially in different applications. Federated Learning (FL) refers to collaborative techniques that avoid the exchange of raw data ...