Purdue faculty dedicate countless hours to exploring the frontiers of their respective fields, pushing the boundaries of knowledge and contributing to the ever-evolving landscape of academia. To ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

The International Conference in Optimization and Learning (OLA2024), organized by RIT (Croatia) and the University of Lille (France), focuses on the future challenges of optimization and learning ...

Associate Professor Emiliano Dall’Anese and his research group examined that concept for a paper that recently won the prestigious ‘Best Paper Award’ in the IEEE journal Transactions on Control of ...

Machine learning (ML) and deep learning (DL) as two well-known methods of artificial intelligence (AI) have emerged as powerful tools in extracting insights and patterns from vast amounts of data. In ...