Video, as a key driver in the global explosion of digital information, can create tremendous
benefits for human society. Governments and enterprises are deploying innumerable …

To bridge the knowledge gap between research and practice, we present the first empirical
study on 16,500 the most popular Android apps, demystifying how smartphone apps exploit …

This paper presents a solution to the challenge of mitigating carbon emissions from hosting
large-scale machine learning (ML) inference services. ML inference is critical to modern …

On-device learning is a promising technique for emerging privacy-preserving machine
learning paradigms. However, through quantitative experiments, we find that commodity …

Text-to-image generation using diffusion models has seen explosive popularity owing to
their ability in producing high quality images adhering to text prompts. However, diffusion …

Deploying deep learning (DL) on mobile devices has been a notable trend in recent years.
To support fast inference of on-device DL, DL libraries play a critical role as algorithms and …

Due to their on-body and ubiquitous nature, wearables can generate a wide range of unique
sensor data creating countless opportunities for deep learning tasks. We propose …

As Video Streaming and Analytics (VSA) systems become increasingly popular, serious
privacy concerns have risen on exposing too much unnecessary private information to the …

The integration of the Internet of Things (IoT) and modern Artificial Intelligence (AI) has given
rise to a new paradigm known as the Artificial Intelligence of Things (AIoT). In this survey, we …

Object detection is crucial in video analytics pipelines, but there is a need to optimize deep
neural networks (DNNs)-based object detection for resource-constrained Internet of Things …