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Richard Byrd
Richard Byrd
Verified email at colorado.edu
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Cited by
Cited by
Year
A limited memory algorithm for bound constrained optimization
RH Byrd, P Lu, J Nocedal, C Zhu
SIAM Journal on scientific computing 16 (5), 1190-1208, 1995
73181995
Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization
C Zhu, RH Byrd, P Lu, J Nocedal
ACM Transactions on mathematical software (TOMS) 23 (4), 550-560, 1997
39601997
An interior point algorithm for large-scale nonlinear programming
RH Byrd, ME Hribar, J Nocedal
SIAM Journal on Optimization 9 (4), 877-900, 1999
22821999
A trust region method based on interior point techniques for nonlinear programming
RH Byrd, JC Gilbert, J Nocedal
Mathematical programming 89, 149-185, 2000
21142000
Knitro: An Integrated Package for Nonlinear Optimization
RH Byrd, J Nocedal, RA Waltz
Large-scale nonlinear optimization, 35-59, 2006
14202006
Representations of quasi-Newton matrices and their use in limited memory methods
RH Byrd, J Nocedal, RB Schnabel
Mathematical Programming 63 (1), 129-156, 1994
10391994
A stochastic quasi-Newton method for large-scale optimization
RH Byrd, SL Hansen, J Nocedal, Y Singer
SIAM Journal on Optimization 26 (2), 1008-1031, 2016
5722016
Approximate solution of the trust region problem by minimization over two-dimensional subspaces
RH Byrd, RB Schnabel, GA Shultz
Mathematical programming 40 (1), 247-263, 1988
5711988
A tool for the analysis of quasi-Newton methods with application to unconstrained minimization
RH Byrd, J Nocedal
SIAM Journal on Numerical Analysis 26 (3), 727-739, 1989
5571989
A trust region algorithm for nonlinearly constrained optimization
RH Byrd, RB Schnabel, GA Shultz
SIAM Journal on Numerical Analysis 24 (5), 1152-1170, 1987
5121987
Global convergence of a cass of quasi-Newton methods on convex problems
RH Byrd, J Nocedal, YX Yuan
SIAM Journal on Numerical Analysis 24 (5), 1171-1190, 1987
4971987
A stable and efficient algorithm for nonlinear orthogonal distance regression
PT Boggs, RH Byrd, RB Schnabel
SIAM Journal on Scientific and Statistical Computing 8 (6), 1052-1078, 1987
4931987
Sample size selection in optimization methods for machine learning
RH Byrd, GM Chin, J Nocedal, Y Wu
Mathematical programming 134 (1), 127-155, 2012
4462012
A family of trust-region-based algorithms for unconstrained minimization with strong global convergence properties
GA Shultz, RB Schnabel, RH Byrd
SIAM Journal on Numerical analysis 22 (1), 47-67, 1985
3921985
Algorithm 676: ODRPACK: software for weighted orthogonal distance regression
PT Boggs, JR Donaldson, R Byrd, RB Schnabel
ACM Transactions on Mathematical Software (TOMS) 15 (4), 348-364, 1989
3241989
On the use of stochastic hessian information in optimization methods for machine learning
RH Byrd, GM Chin, W Neveitt, J Nocedal
SIAM Journal on Optimization 21 (3), 977-995, 2011
3022011
User's reference guide for odrpack version 2.01: Software for weighted orthogonal distance regression
PT Boggs, PT Boggs, JE Rogers, RB Schnabel
US Department of Commerce, National Institute of Standards and Technology, 1992
2571992
Exact and inexact subsampled Newton methods for optimization
R Bollapragada, RH Byrd, J Nocedal
IMA Journal of Numerical Analysis 39 (2), 545-578, 2019
1932019
An algorithm for nonlinear optimization using linear programming and equality constrained subproblems
RH Byrd, NIM Gould, J Nocedal, RA Waltz
Mathematical Programming 100 (1), 27-48, 2003
1852003
A theoretical and experimental study of the symmetric rank-one update
HF Khalfan, RH Byrd, RB Schnabel
SIAM Journal on Optimization 3 (1), 1-24, 1993
1631993
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