259 citations · 2.9k across the 123 of their papers we have counts for
15 papers · 1 filter
Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems
Yuchen Fang, Sen Na, Michael W. Mahoney +1
We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems with stochastic objectives and deterministic eq…
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
Sen Na, Michael W. Mahoney
We consider online statistical inference of constrained stochastic nonlinear optimization problems. We apply the Stochastic Sequential Quadratic Programming (StoSQP) method to solv…
Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence
Sen Na, Michał Dereziński, Michael W. Mahoney
We consider minimizing a smooth and strongly convex objective function using a stochastic Newton method. At each iteration, the algorithm is given an oracle access to a stochastic…
Inexact Newton-CG Algorithms With Complexity Guarantees
Zhewei Yao, Peng Xu, Fred Roosta +2
We consider variants of a recently-developed Newton-CG algorithm for nonconvex problems \citep{royer2018newton} in which inexact estimates of the gradient and the Hessian informati…
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update
Michał Dereziński, Jonathan Lacotte, Mert Pilanci +1
In second-order optimization, a potential bottleneck can be computing the Hessian matrix of the optimized function at every iteration. Randomized sketching has emerged as a powerfu…
Newton-MR: Inexact Newton Method With Minimum Residual Sub-problem Solver
Fred Roosta, Yang Liu, Peng Xu +1
We consider a variant of inexact Newton Method, called Newton-MR, in which the least-squares sub-problems are solved approximately using Minimum Residual method. By construction, N…