MMH Shuvo, SK Islam, J Cheng… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted in breakthroughs in many areas. However, deploying these highly accurate models for data …
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial …
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on …
YG Kim, CJ Wu - MICRO-54: 54th Annual IEEE/ACM International …, 2021 - dl.acm.org
Federated learning enables a cluster of decentralized mobile devices at the edge to collaboratively train a shared machine learning model, while keeping all the raw training …
C Wang, Y Yang, P Zhou - IEEE Transactions on Parallel and …, 2020 - ieeexplore.ieee.org
Originated from distributed learning, federated learning enables privacy-preserved collaboration on a new abstracted level by sharing the model parameters only. While the …
M Schule, H Lang, M Springer, A Kemper… - Proceedings of the 33rd …, 2021 - dl.acm.org
In machine learning, continuously retraining a model guarantees accurate predictions based on the latest data as training input. But to retrieve the latest data from a database, time …
Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on …
Y Zhang, T Gu, X Zhang - Proceedings of the 18th Conference on …, 2020 - dl.acm.org
Mobile Deep Learning (MDL) has emerged as a privacy-preserving learning paradigm for mobile devices. This paradigm offers unique features such as privacy preservation …
In the wake of COVID-19, rising monkeypox cases pose a potential pandemic threat. While less severe than COVID-19, its increasing spread underscores the urgency of early …