Reinforcement Learning (RL) has emerged as a highly effective technique for addressing
various scientific and applied problems. Despite its success, certain complex tasks remain …

Labeled data can be expensive to acquire in several application domains, including medical
imaging, robotics, and computer vision. To efficiently train machine learning models under …

Bayesian optimization (BO) has well-documented merits for optimizing black-box functions
with an expensive evaluation cost. Such functions emerge in applications as diverse as …

Graph-guided semi-supervised learning (SSL) has gained popularity in several network
science applications, including biological, social, and financial ones. SSL becomes …

Cardiovascular disease (CVD) poses a significant global health challenge, and accurate
inference methods are vital for early detection and intervention. However, the quality of …

Quota is often used in resource allocation and management scenarios to prevent abuse of
resource and increase the efficiency of resource utilization. Quota management is usually …

Abstract Machine learning (ML) has gained popularity due to its well-documented merits in
several inference tasks across diverse applications including healthcare, robotics and …

Distributed learning has attracted extensive interest in recent years, owing to the explosion
of data generated from mobile sensors, social media services, and other networked multi …