Marina Evangelou

Orcid: 0000-0003-0789-8944

According to our database1, Marina Evangelou authored at least 16 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Multi-view data visualisation <i>via</i> manifold learning.
PeerJ Comput. Sci., 2024

Dual feature reduction for the sparse-group lasso and its adaptive variant.
CoRR, 2024

Strong screening rules for group-based SLOPE models.
CoRR, 2024

Logistic Variational Bayes Revisited.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
Variational Bayes for high-dimensional proportional hazards models with applications within gene expression.
Bioinform., 2022

2021
Multi-type relational clustering for enterprise cyber-security networks.
Pattern Recognit. Lett., 2021

S-multi-SNE: Semi-Supervised Classification and Visualisation of Multi-View Data.
CoRR, 2021

Multi-view Data Visualisation via Manifold Learning.
CoRR, 2021

2020
An anomaly detection framework for cyber-security data.
Comput. Secur., 2020

Integrating multi-OMICS data through sparse canonical correlation analysis for the prediction of complex traits: a comparison study.
Bioinform., 2020

2018
Adaptive Anomaly Detection on Network Data Streams.
Proceedings of the 2018 IEEE International Conference on Intelligence and Security Informatics, 2018

2017
Clustering and monitoring edge behaviour in enterprise network traffic.
Proceedings of the 2017 IEEE International Conference on Intelligence and Security Informatics, 2017

2016
Activity-based temporal anomaly detection in enterprise-cyber security.
Proceedings of the IEEE Conference on Intelligence and Security Informatics, 2016

Predictability of NetFlow data.
Proceedings of the IEEE Conference on Intelligence and Security Informatics, 2016

The Time-Varying Dependency Patterns of NetFlow Statistics.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2014
Two novel pathway analysis methods based on a hierarchical model.
Bioinform., 2014


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