The document provides an overview of the coordinate descent method for minimizing convex functions. It discusses how coordinate descent works by iteratively minimizing a function with respect to one variable at a time while holding others fixed. The summary also notes that coordinate descent converges to a stationary point for continuously differentiable functions and has advantages like easy implementation and ability to handle large-scale problems, though it may be slower than other methods near the optimum.