Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

The role of data in building AI systems has recently been significantly magnified by the
emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model …

In recent years, deep neural networks have been successful in both industry and academia,
especially for computer vision tasks. The great success of deep learning is mainly due to its …

Games are abstractions of the real world, where artificial agents learn to compete and
cooperate with other agents. While significant achievements have been made in various …

Graph data are pervasive in many real-world applications. Recently, increasing attention
has been paid on graph neural networks (GNNs), which aim to model the local graph …

In mobile edge computing (MEC) systems, unmanned aerial vehicles (UAVs) facilitate edge
service providers (ESPs) offering flexible resource provisioning with broader communication …

High false-positive rate is a long-standing challenge for anomaly detection algorithms,
especially in high-stake applications. To identify the true anomalies, in practice, analysts or …

In the last decade, many deep learning models have been well trained and made a great
success in various fields of machine intelligence, especially for computer vision and natural …

In this paper, we study a defense against poisoned encoders in SSL called distillation, which
is a defense used in supervised learning originally. Distillation aims to distill knowledge from …

Multi-agent systems (MAS) are widely prevalent and crucially important in numerous real-
world applications, where multiple agents must make decisions to achieve their objectives in …