Approximation Theory and the Design of Fast Algorithms

We survey key techniques and results from approximation theory in the context of uniform approximations to real functions such as e^{-x}, 1/x, and x^k. We then present a selection of results demonstrating how such approximations can be used to speed up primitives crucial for the design of fast algorithms for problems such as simulating random walks, graph partitioning, solving linear system of equations, computing eigenvalues and combinatorial approaches to solve semi-definite programs.