Convergence of the Gradient Method in Normed Linear Spaces.

RH Byrd , Richard A Tapia , WISCONSIN UNIV MADISON MATHEMATICS RESEARCH CENTER

1974
New Methods for Large Scale Local and Global Optimization

Richard Byrd , Robert Schnabel , COLORADO UNIV AT BOULDER
colo

1994
New Methods for Nonlinear Optimization

Robert B Schnabel , Richard H Byrd , COLORADO UNIV AT BOULDER DEPT OF COMPUTER SCIENCE

1994
A Stochastic Quasi-Newton Method for Large-Scale Optimization

J. Nocedal , R. H. Byrd , S. L. Hansen , Y. Singer
arXiv: Optimization and Control

29
2014
Limited Memory BFGS Minimizer with Bounds on Parameters

Jorge Nocedal , Ciyou Zhu , Richard Byrd , Jose Luis Morales

1
2015
Preconditioning the limited-memory bfgs algorithm

Richard H. Byrd , Lianjun Jiang
University of Colorado at Boulder

1
2006
Exact and Inexact Subsampled Newton Methods for Optimization

Jorge Nocedal , Richard Byrd , Raghu Bollapragada
arXiv: Optimization and Control

28
2016
PARALLEL QUASI-NEWTON M ETHODS FOR UNCONSTRAINED O PTIMIZATION

Gerald A. Shultz , Richard H. Byrd , B. Schnabel

1988
A Preconditioned L-BFGS Algorithm with Application to Molecular Energy Minimization ; CU-CS-982-04

Elizabeth Eskow , Robert B Schnabel , Richard H Byrd , Lianjun Jiang

3
2004
Adaptive Sampling Strategies for Stochastic Optimization

Jorge Nocedal , Richard Byrd , Raghu Bollapragada
arXiv: Optimization and Control

8
2017
Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods

Jorge Nocedal , Richard H. Byrd , Albert S. Berahas
arXiv: Optimization and Control

2
2018
Analysis of the BFGS Method with Errors

Jorge Nocedal , Richard Byrd , Yuchen Xie
arXiv: Optimization and Control

2019
An Algorithm for Quadratic $\ell_1$-Regularized Optimization with a Flexible Active-Set Strategy

Jorge Nocedal , Richard Byrd , Stefan Solntsev
arXiv: Optimization and Control

2014