Block BFGS Methods

We introduce a quasi-Newton method with block updates called Block BFGS. We show that this method, performed with inexact Armijo-Wolfe line searches, converges globally and superlinearly under the same convexity assumptions as BFGS. We also show that Block BFGS is globally convergent to a stationary point when applied to non-convex functions with bounded Hessian, and discuss other modifications for non-convex minimization. Numerical experiments comparing Block BFGS, BFGS and gradient descent are presented.

Citation

manuscript, Dept. of Industrial Engineering and Operations Research, Columbia University, New York, NY, Sept 2016.

Article

Download

View Block BFGS Methods