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Fusing Deep Learning and Optimization

Dr. Pascal Van Hentenryck
NSF AI Institute for Advances in Optimization
Friday, October 27, 2023
1:50-2:40pm Tickle 500

Abstract: The fusion of deep learning and optimization has the potential to
deliver outcomes for engineering applications that the two technologies cannot achieve independently. This talk illustrates this potential with the concept of optimization proxy, a differentiable program that can produce, in milliseconds, feasible (or near-feasible) and near-optimal solutions to classes of optimization problems. The talk reviews some of the foundations underlying optimization proxies,
including end-to-end learning, compact optimization learning, dual
learning, and self-supervised learning. The benefits of optimization
proxies are demonstrated on applications in power systems and supply

Bio: Pascal Van Hentenryck is the director of the NSF AI Institute for
Advances in Optimization (AI4OPT) and the A. Russell Chandler III
Chair and Professor at the Georgia Institute of Technology. Several of
his optimization systems have been in commercial use for more than 20
years. His current research focuses on AI for Engineering, fusing
machine learning and optimization for applications in energy systems,
supply chains and manufacturing, and mobility. Van Hentenryck is a
fellow of AAAI and INFORMS, and the recipients of numerous research
and teaching awards. He was also a Ulam fellow at the Los Alamos
National Laboratories.