Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

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 …

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 …

Originated from distributed learning, federated learning enables privacy-preserved
collaboration on a new abstracted level by sharing the model parameters only. While the …

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 …

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 …