[gov3009-l] Gov 3009: Applied Stats Workshop: 1/28

Hi everyone! This week at the Applied Statistics Workshop we will be welcoming *Jelani Nelson*, a Professor of Computer Science at the Harvard School of Engineering and Applied Sciences. He will be presenting work entitled *Dimensionality Reduction Via Sparse Matrices*. Please find the abstract below and on the website here <http://projects.iq.harvard.edu/applied.stats.workshop-gov3009/presentations/presenter-jelani-nelson-dimensionality-reduction-sparse> As usual, we will meet in CGIS Knafel Room 354 and lunch will be provided. Hope to see you all there! -- Anton Strezhnev Title: Dimensionality Reduction Via Sparse Matrices Abstract: This talk will discuss sparse Johnson-Lindenstrauss transforms, i.e. sparse linear maps into much lower dimension which preserve the Euclidean geometry of a set of vectors. Both upper and lower bounds will be presented, as well as applications to certain domains such as numerical linear algebra and compressed sensing. Based on various joint works with Jean Bourgain, Daniel M. Kane, and Huy Le Nguyen.