  We derive exponential tail inequalities for sums of random matrices with no
dependence on the explicit matrix dimensions. These are similar to the matrix
versions of the Chernoff bound and Bernstein inequality except with the
explicit matrix dimensions replaced by a trace quantity that can be small even
when the dimension is large or infinite. Some applications to principal
component analysis and approximate matrix multiplication are given to
illustrate the utility of the new bounds.
