Juan Marcelo Parra Ullauri

IEEE Netw., March, 2024

kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud-edge environments.

[BibT_eX]

[DOI]

Adrian-Cristian Nicolaescu

Hari Madhukumar

Future Gener. Comput. Syst., 2024

Federated Fairness Analytics: Quantifying Fairness in Federated Learning.

[BibT_eX]

[DOI]

Oscar Dilley

Rasheed Hussain

CoRR, 2024

Federated Transfer Component Analysis Towards Effective VNF Profiling.

[BibT_eX]

[DOI]

Xunzheng Zhang

Shadi Moazzeni

CoRR, 2024

Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities.

[BibT_eX]

[DOI]

CoRR, 2024

Exploring the Synergy of Fog Computing, Blockchain, and Federated Learning for IoT Applications: A Systematic Literature Review.

[BibT_eX]

[DOI]

Wilson Valdez Solis

Attila Kertész

IEEE Access, 2024

Joint Network and Computing Resource Optimisation in Distributed Quantum Computing.

[BibT_eX]

[DOI]

Sima Bahrani

Rui Wang

Romerson Deiny Oliveira

Proceedings of the Optical Fiber Communications Conference and Exhibition, 2024

GAN-Based Privacy Abuse Attack on Federated Learning in IoT Networks.

[BibT_eX]

[DOI]

Runzhe Hao

Rasheed Hussain

Xenofon Vasilakos

Proceedings of the IEEE INFOCOM 2024, 2024

AI Model Placement for 6G Networks Under Epistemic Uncertainty Estimation.

[BibT_eX]

[DOI]

Liming Huang

Yulei Wu

Proceedings of the IEEE International Conference on Communications, 2024

2023

A Framework for History-Aware Hyperparameter Optimisation in Reinforcement Learning.

[BibT_eX]

[DOI]

Chen Zhen

CoRR, 2023

Federated Hyperparameter Optimisation with Flower and Optuna.

[BibT_eX]

[DOI]

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

Privacy Preservation in Kubernetes-based Federated Learning: A Networking Approach.

[BibT_eX]

[DOI]

Proceedings of the IEEE INFOCOM 2023, 2023

2022

Reward-Reinforced Generative Adversarial Networks for Multi-Agent Systems.

[BibT_eX]

[DOI]

Changgang Zheng

Shufan Yang

IEEE Trans. Emerg. Top. Comput. Intell., 2022

Event-driven temporal models for explanations - ETeMoX: explaining reinforcement learning.

[BibT_eX]

[DOI]

Softw. Syst. Model., 2022

History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings, 2022

2021

Reward-Reinforced Reinforcement Learning for Multi-agent Systems.

[BibT_eX]

[DOI]

Changgang Zheng

Shufan Yang

CoRR, 2021

Towards an architecture integrating complex event processing and temporal graphs for service monitoring.

[BibT_eX]

[DOI]

Juan Boubeta-Puig

Guadalupe Ortiz

Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems.

[BibT_eX]

[DOI]

Proceedings of the ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, 2021

2020

Temporal Models for History-Aware Explainability.

[BibT_eX]

[DOI]

Proceedings of the SAM '20: 12th System Analysis and Modelling Conference, 2020

2019

Towards History-Aware Self-Adaptation with Explanation Capabilities.

[BibT_eX]

[DOI]

Proceedings of the IEEE 4th International Workshops on Foundations and Applications of Self* Systems, 2019

Querying and Annotating Model Histories with Time-Aware Patterns.

[BibT_eX]

[DOI]