Jelani Nelson: Dimensionality reduction via sparse matrices.

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. Applications to certain domains will also be presented, such as to numerical linear algebra.

Based on joint works with Daniel Kane (Stanford) and Huy Nguyen (Princeton).