CS Seminar: Ben Moseley

Description

Ben Moseley, an associate professor of operations research at Carnegie Mellon University, will give a talk titled "Machine Learning for Faster Optimization" for the Department of Computer Science.

Abstract:

This talk will discuss the area of algorithms with predictions, also known as learning-augmented algorithms. These methods parameterize algorithms with machine-learned predictions, enabling the algorithms to tailor their decisions to input distributions and to allow for improved performance on runtime, space, or solution quality. This talk will discuss recent developments on how to leverage machine-learned predictions to improve the runtime efficiency of algorithms for optimization and data structures. The talk will also discuss how to achieve "instance-optimal" algorithms when the predictions are accurate and the algorithm's performance gracefully degrades when there are errors in the predicted advice. The talk will illustrate via examples such as bipartite matching the potential of the area to realize significant performance improvements for algorithm efficiency.