May 3, 2024 · The evaluation metric encompasses various aspects including accuracy, convergence, computational efficiency, fairness, and personalization.
May 3, 2024 · To mitigate the research gap, we introduce holistic evaluation metrics (HEM) and a corresponding evaluation pipeline to thoroughly assess FL ...
To mitigate this research gap, we introduce the Holistic Evaluation Metrics (HEM) for FL in this work. Specifically, we collectively focus on three primary use ...
Bibliographic details on Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning.
Sep 30, 2024 · In this work, we consider the application scenarios of IoT, Smartphones, and Institutions as the principal FL use cases.
Missing: Sensitive | Show results with:Sensitive
May 6, 2024 · The paper proposes the Holistic Evaluation Metrics (HEM) framework to comprehensively evaluate federated learning (FL) algorithms across three ...
Use Case Sensitive Evaluation Metrics for Federated Learning | Bytez
bytez.com › docs › arxiv › paper
This research paper introduces a new way to evaluate Federated Learning (FL) algorithms called Holistic Evaluation Metrics (HEM).
People also ask
What is evaluation metrics in NLP?
What are some common metrics for evaluating classification models?
What are evaluation metrics?
Connected Papers is a visual tool to help researchers and applied scientists find academic papers relevant to their field of work.
The paper introduces Holistic Evaluation Metrics (HEM) to comprehensively evaluate Federated Learning (FL) algorithms across diverse real-world use cases, ...
Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning · no code implementations • 3 May 2024 • Yanli Li, Jehad Ibrahim ...