activity
20202026
most citedRegularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation

8 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Stealthy Poisoning Attacks Bypass Defenses in Regression Settings

Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer +1

Regression models are widely used in industrial processes, engineering, and in natural and physical sciences, yet their robustness to poisoning has received less attention. When it…

cs.LG2023

Hyperparameter Learning under Data Poisoning: Analysis of the Influence of Regularization via Multiobjective Bilevel Optimization

Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer +1

Machine Learning (ML) algorithms are vulnerable to poisoning attacks, where a fraction of the training data is manipulated to deliberately degrade the algorithms' performance. Opti…

cs.LG2022★ 3 cited

Explainability in Deep Reinforcement Learning, a Review into Current Methods and Applications

Thomas Hickling, Abdelhafid Zenati, Nabil Aouf +1

The use of Deep Reinforcement Learning (DRL) schemes has increased dramatically since their first introduction in 2015. Though uses in many different applications are being found,…

cs.LG2022★ 3 cited

Robust Adversarial Attacks Detection based on Explainable Deep Reinforcement Learning For UAV Guidance and Planning

Thomas Hickling, Nabil Aouf, Phillippa Spencer

The dangers of adversarial attacks on Uncrewed Aerial Vehicle (UAV) agents operating in public are increasing. Adopting AI-based techniques and, more specifically, Deep Learning (D…

cs.LG2021★ 3 cited

Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters

Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer +1

Machine learning algorithms are vulnerable to poisoning attacks, where a fraction of the training data is manipulated to degrade the algorithms' performance. We show that current a…

cs.LG2020★ 8 cited

Regularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation

Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer +1

Machine Learning (ML) algorithms are vulnerable to poisoning attacks, where a fraction of the training data is manipulated to deliberately degrade the algorithms' performance. Opti…