Deep Learning for Unrelated-Machines Scheduling: Handling Variable Dimensions

This article likely discusses the application of deep learning techniques to optimize scheduling tasks on machines that are not necessarily identical. The focus on "variable dimensions" suggests the research addresses the challenge of handling scheduling problems where the number of machines, tasks, or other parameters can change. The source, ArXiv, indicates this is a pre-print or research paper.