Sponsored by the Rutgers University Department of Mathematics and the
Center for Discrete Mathematics and Theoretical Computer Science (DIMACS)

Doron Zeilberger, Rutgers University, zeilberg {at} math [dot] rutgers [dot] edu
Nathan Fox, Rutgers University, fox {at} math [dot] rutgers [dot] edu)

Combinatorics of Distance Covariance: Inclusion-Minimal Maximizers of Quasi-Concave Set Functions for Diverse Variable Selection

Speaker: Praneeth Vepakomma ,Motorola Solutions

Date: Thursday, March 9, 2017 5:00pm

Location: Hill Center, Room 705, Rutgers University, Busch Campus, Piscataway, NJ


'Distance Covariance' is a popular measure of statistical dependence between random variables. In this talk I'd provide an algorithm to combinatorially choose subset(s) of random variables that are least statistically dependent on each other in terms of their distance covariances. Some applications of our framework to regression problems in statistics would also be discussed. Required conditions for our framework to be applicable to combinatorial optimization problems would also be shared. This is joint work done with Yulia Kempner.

See: http://www.math.rutgers.edu/~nhf12/expmath/