AI for Solving Real Large-Scale Decision Problems
The field of Artificial Intelligence (AI) is flourishing and AI technologies are becoming part of people's everyday life. The success can to a large extent be attributed to breakthroughs in machine learning (ML) and in particular deep learning. ML algorithms have had remarkable success in automating tasks that are easy to accomplish but difficult to formalize by humans, for example, image analysis, natural language processing, voice and face recognition.
On the other hand, the field of Operations Research (OR) has been successful in developing methodologies to solve efficiently various types of decision problems that can be formalized but are nevertheless too complex or time consuming for humans to process. These methodologies are crucial to a wealth of applications.
In this talk we give a brief introduction to ML and OR with a special focus on novel AI methodologies at the intersection between ML and discrete optimization. We give a high-level presentation of such a methodology where OR and ML complement each other to address an overall decision problem that could not be solved otherwise. It is applied to a container loading problem faced by North American railroads.
The talk will be held by Emma Frejinger, Associate Professor in the Department of Computer Science and Operations Research at Université de Montréal.
The event is free of charge, but your registration is needed.