In this work, we address a question that has attracted intense interest in recent years: whether machine learning-assisted algorithms can genuinely outperform classical approaches in challenging ...

Abstract: In this paper, we investigate the problem of decomposing 2D environments for robot coverage path planning (CPP). CPP involves computing a cost-minimizing path so that the robot’s coverage or ...

Abstract: Smart cities use internet to make the day-to-day living of city inhabitants more comfortable and secure. In this regard, long-range wide area networks (LoRaWAN) are ideally suited to provide ...

Department of Computer Science and Engineering, College of Engineering, The Ohio State University, Columbus, Ohio 43210, United States Translational Data Analytics Institute, The Ohio State University ...

Reinforcement learning (RL) has emerged as a dynamic and transformative paradigm in artificial intelligence, offering the promise of intelligent decision-making in complex and dynamic environments.

This valuable study reports novel active learning batch selection methods that have been applied to optimization tasks related to ADMET and affinity properties relevant within the drug discovery field ...

This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, ...