1 citations · 1 across the 1 of their papers we have counts for
4 papers
Federated Fairness Analytics: Quantifying Fairness in Federated Learning
Oscar Dilley, Juan Marcelo Parra-Ullauri, Rasheed Hussain +1
Federated Learning (FL) is a privacy-enhancing technology for distributed ML. By training models locally and aggregating updates - a federation learns together, while bypassing cen…
AI Model Placement for 6G Networks under Epistemic Uncertainty Estimation
Liming Huang, Yulei Wu, Juan Marcelo Parra-Ullauri +2
The adoption of Artificial Intelligence (AI) based Virtual Network Functions (VNFs) has witnessed significant growth, posing a critical challenge in orchestrating AI models within…
Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities
Juan Marcelo Parra-Ullauri, Xunzheng Zhang, Anderson Bravalheri +3
Extensive research is underway to meet the hyper-connectivity demands of 6G networks, driven by applications like XR/VR and holographic communications, which generate substantial d…
A Framework for History-Aware Hyperparameter Optimisation in Reinforcement Learning
Juan Marcelo Parra-Ullauri, Chen Zhen, Antonio García-Domínguez +5
A Reinforcement Learning (RL) system depends on a set of initial conditions (hyperparameters) that affect the system's performance. However, defining a good choice of hyperparamete…