ORIE Colloquium: Andrés Gómez (USC)

Real time solution of quadratic optimization problems with banded matrices and indicator variables

We consider mixed-integer quadratic optimization problems with banded matrices and indicator variables. These problems arise pervasively in statistical inference problems with time-series data, where the banded matrix captures the temporal relationship of the underlying process. In particular, the problem studied arises in monitoring problems, where the decision-maker wants to detect changes or anomalies. We propose to solve these problems using decision diagrams. In particular we show how to exploit the temporal dependencies to construct diagrams with size polynomial in the number of decision variables. We also describe how to construct the convex hull of the set under study from the decision diagrams, and how to deploy the method online to solve the problems in milliseconds via a shortest path algorithm.

Bio:
Andrés Gómez received his B.S. in mathematics and B.S. in computer science from the Universidad de los Andes (Colombia) and obtained his M.S. and Ph.D. in industrial engineering and operations research from the University of California Berkeley. He currently is an assistant professor in the Department of Industrial and Systems Engineering at the University of Southern California.

Prof. Gómez research focuses on developing new theory and tools for challenging optimization problems and their applications in statistics and machine learning. His research has been supported by numerous grants from the National Science Foundation, the Air Force Office of Scientific Research (including a YIP award), Google and Meta.