425 citations · 1.1k across the 32 of their papers we have counts for
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Quasi-Newton Methods: Superlinear Convergence Without Line Searches for Self-Concordant Functions
Wenbo Gao, Donald Goldfarb
We consider the use of a curvature-adaptive step size in gradient-based iterative methods, including quasi-Newton methods, for minimizing self-concordant functions, extending an ap…
Block BFGS Methods
Wenbo Gao, Donald Goldfarb
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 superli…
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
Xiao Wang, Shiqian Ma, Donald Goldfarb +1
In this paper we study stochastic quasi-Newton methods for nonconvex stochastic optimization, where we assume that noisy information about the gradients of the objective function i…
Stochastic Block BFGS: Squeezing More Curvature out of Data
Robert M. Gower, Donald Goldfarb, Peter Richtárik
We propose a novel limited-memory stochastic block BFGS update for incorporating enriched curvature information in stochastic approximation methods. In our method, the estimate of…
Semi-Stochastic Frank-Wolfe Algorithms with Away-Steps for Block-Coordinate Structure Problems
Donald Goldfarb, Garud Iyengar, Chaoxu Zhou
We propose a semi-stochastic Frank-Wolfe algorithm with away-steps for regularized empirical risk minimization and extend it to problems with block-coordinate structure. Our algori…