A survey of machine learning techniques applied to software defined networking (SDN): Research issues and challenges

J Xie, FR Yu, T Huang, R Xie, J Liu… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
In recent years, with the rapid development of current Internet and mobile communication
technologies, the infrastructure, devices and resources in networking systems are becoming …

[PDF][PDF] Fake news: A survey of research, detection methods, and opportunities

X Zhou, R Zafarani - arXiv preprint arXiv:1812.00315, 2018 - academia.edu
arXiv:1812.00315v1 [cs.CL] 2 Dec 2018 Page 1 Fake News: A Survey of Research,
Detection Methods, and Opportunities XINYI ZHOU, Syracuse University, USA REZA …

The use of machine learning algorithms in recommender systems: A systematic review

I Portugal, P Alencar, D Cowan - Expert Systems with Applications, 2018 - Elsevier
Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …

Machine learning for network automation: overview, architecture, and applications [Invited Tutorial]

D Rafique, L Velasco - Journal of Optical Communications and …, 2018 - ieeexplore.ieee.org
Networks are complex interacting systems involving cloud operations, core and metro
transport, and mobile connectivity all the way to video streaming and similar user …

Boosting self-supervised learning via knowledge transfer

M Noroozi, A Vinjimoor, P Favaro… - Proceedings of the …, 2018 - openaccess.thecvf.com
In self-supervised learning one trains a model to solve a so-called pretext task on a dataset
without the need for human annotation. The main objective, however, is to transfer this …

A review on conventional machine learning vs deep learning

NK Chauhan, K Singh - 2018 International conference on …, 2018 - ieeexplore.ieee.org
In now days, deep learning has become a prominent and emerging research area in
computer vision applications. Deep learning permits the multiple layers models for …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

The impact of automated parameter optimization on defect prediction models

C Tantithamthavorn, S McIntosh… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Defect prediction models-classifiers that identify defect-prone software modules-have
configurable parameters that control their characteristics (eg, the number of trees in a …

Geographic object-based image analysis (GEOBIA): Emerging trends and future opportunities

G Chen, Q Weng, GJ Hay, Y He - GIScience & Remote Sensing, 2018 - Taylor & Francis
Over the last two decades (since ca. 2000), Geographic Object-Based Image Analysis
(GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote …

Evaluation of machine learning methods for formation lithology identification: A comparison of tuning processes and model performances

Y Xie, C Zhu, W Zhou, Z Li, X Liu, M Tu - Journal of Petroleum Science and …, 2018 - Elsevier
Identification of underground formation lithology from well log data is an important task in
petroleum exploration and engineering. Recently, several computational algorithms have …