Richard Byrd
Richard Byrd
Verified email at colorado.edu
TitleCited byYear
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
41891995
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
21391997
An interior point algorithm for large-scale nonlinear programming
RH Byrd, ME Hribar, J Nocedal
SIAM Journal on Optimization 9 (4), 877-900, 1999
14591999
A trust region method based on interior point techniques for nonlinear programming
RH Byrd, JC Gilbert, J Nocedal
Mathematical programming 89 (1), 149-185, 2000
13142000
Knitro: An Integrated Package for Nonlinear Optimization
RH Byrd, J Nocedal, RA Waltz
Large-scale nonlinear optimization, 35-59, 2006
8442006
Representations of quasi-Newton matrices and their use in limited memory methods
RH Byrd, J Nocedal, RB Schnabel
Mathematical Programming 63 (1-3), 129-156, 1994
7941994
Approximate solution of the trust region problem by minimization over two-dimensional subspaces
RH Byrd, RB Schnabel, GA Shultz
Mathematical programming 40 (1-3), 247-263, 1988
4191988
A trust region algorithm for nonlinearly constrained optimization
RH Byrd, RB Schnabel, GA Shultz
SIAM Journal on Numerical Analysis 24 (5), 1152-1170, 1987
4081987
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
4071989
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
3911987
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
3881987
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
3391985
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
2432016
Sample size selection in optimization methods for machine learning
RH Byrd, GM Chin, J Nocedal, Y Wu
Mathematical programming 134 (1), 127-155, 2012
2142012
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
1921992
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
1712011
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
1432003
An analysis of reduced Hessian methods for constrained optimization
RH Byrd, J Nocedal
Mathematical Programming 49 (1-3), 285-323, 1990
1341990
Parallel quasi-Newton methods for unconstrained optimization
RH Byrd, RB Schnabel, GA Shultz
Mathematical Programming 42 (1-3), 273-306, 1988
1161988
Robust trust region methods for constrained optimization
RH Byrd
Third SIAM Conference on Optimization, Houston, Texas, 1987
1111987
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