425 citations · 1.1k across the 32 of their papers we have counts for
19 papers · 1 filter
ADMM for Multiaffine Constrained Optimization
Wenbo Gao, Donald Goldfarb, Frank E. Curtis
We expand the scope of the alternating direction method of multipliers (ADMM). Specifically, we show that ADMM, when employed to solve problems with multiaffine constraints that sa…
Unbiased Simulation for Optimizing Stochastic Function Compositions
Jose Blanchet, Donald Goldfarb, Garud Iyengar +2
In this paper, we introduce an unbiased gradient simulation algorithms for solving convex optimization problem with stochastic function compositions. We show that the unbiased grad…
Using Negative Curvature in Solving Nonlinear Programs
Donald Goldfarb, Cun Mu, John Wright +1
Minimization methods that search along a curvilinear path composed of a non-ascent nega- tive curvature direction in addition to the direction of steepest descent, dating back to t…
Linear Convergence of Stochastic Frank Wolfe Variants
Donald Goldfarb, Garud Iyengar, Chaoxu Zhou
In this paper, we show that the Away-step Stochastic Frank-Wolfe Algorithm (ASFW) and Pairwise Stochastic Frank-Wolfe algorithm (PSFW) converge linearly in expectation. We also sho…
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…