9 citations · 12 across the 8 of their papers we have counts for
6 papers · 1 filter
Profiling AI Models: Towards Efficient Computation Offloading in Heterogeneous Edge AI Systems
Juan Marcelo Parra-Ullauri, Oscar Dilley, Hari Madhukumar +1
The rapid growth of end-user AI applications, such as computer vision and generative AI, has led to immense data and processing demands often exceeding user devices' capabilities.…
Resource Management and Circuit Scheduling for Distributed Quantum Computing Interconnect Networks
Sima Bahrani, Romerson D. Oliveira, Juan Marcelo Parra-Ullauri +2
Distributed quantum computing (DQC) has emerged as a promising approach to overcome the scalability limitations of monolithic quantum processors in terms of computational capabilit…
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…
Federated Transfer Component Analysis Towards Effective VNF Profiling
Xunzheng Zhang, Shadi Moazzeni, Juan Marcelo Parra-Ullauri +2
The increasing concerns of knowledge transfer and data privacy challenge the traditional gather-and-analyse paradigm in networks. Specifically, the intelligent orchestration of Vir…
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…