Deep learning has revolutionized the fields of computer vision, natural language
understanding, speech recognition, information retrieval, and more. However, with the …

The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …

Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

Recent deep learning-based object detectors have shown compelling performance for the
detection of large objects in autonomous driving applications. However, the detection of …

Modern deep neural networks, particularly recent large language models, come with
massive model sizes that require significant computational and storage resources. To …

Continual graph learning is rapidly emerging as an important role in a variety of real-world
applications such as online product recommendation systems and social media. While …

Recently, deep learning has greatly promoted the development of synthetic aperture radar
(SAR) ship detection. But the detectors are usually heavy and computation intensive, which …

Deep neural networks (DNNs) have shown great success in completing complex tasks.
However, DNNs inevitably bring high computational cost and storage consumption due to …

Neural network quantization is a promising compression technique to reduce memory
footprint and save energy consumption, potentially leading to real-time inference. However …

Nonlinear power flow constraints render a variety of power system optimization problems
computationally intractable. Emerging research shows, however, that the nonlinear AC …