Prof. John Lipor
Assistant Professor at Portland State University

Abstract. In this lecture we will discuss a novel approach to the subspace clustering problem that leverages ensembles of the K-subspaces (KSS) algorithm with random initializations. We will extend existing results in subspace clustering to show that correct clustering can be achieved by any algorithm that obtains measurements of any monotonic function of the inner product between points. We then show that a single iteration of KSS with random initialization produces such a measurement, and hence our algorithm can provably recover subspaces under the same conditions as state-of-the-art algorithms. The finding is, to the best of our knowledge, the first recovery guarantee for evidence accumulation clustering and for KSS variants. It also provides insight into random initializations of subspace arrangements.

Biography. John Lipor is an assistant professor in Electrical and Computer Engineering at Portland State University. He received his Ph.D. in Electrical Engineering from the University of Michigan, Ann Arbor in 2017 and was an awardee of the NSF Graduate Research Fellowship. He received his M.S. in Electrical Engineering from the King Abdullah University of Science and Technology (KAUST) in 2013 and his B.S. in Electrical Engineering from the University of Wisconsin, Madison in 2009. His research interests include active learning and subspace methods, with an emphasis on problems in environmental sensing and monitoring.

Parking. Best parrking option is to use the Centergy Parking garage accessible from Spring Street. Optionally, you can park at the Georgia Tech Hotel guest parking or in any metered spot on Tech Square

Agenda

• 12:00 PM - 12:05 PM - Introductions

• 12:05 PM - 12:45 PM - Seminar by Prof. John Lipor

• 12:45 PM - 1:00 PM - Discussion and Q&A

•  1:00 PM -  1:30 PM - Reception and networking