| 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 | 7684 | 1995 |
| 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 | 4185 | 1997 |
| An interior point algorithm for large-scale nonlinear programming RH Byrd, ME Hribar, J Nocedal SIAM Journal on Optimization 9 (4), 877-900, 1999 | 2383 | 1999 |
| A trust region method based on interior point techniques for nonlinear programming RH Byrd, JC Gilbert, J Nocedal Mathematical programming 89, 149-185, 2000 | 2211 | 2000 |
| Knitro: An Integrated Package for Nonlinear Optimization RH Byrd, J Nocedal, RA Waltz Large-scale nonlinear optimization, 35-59, 2006 | 1485 | 2006 |
| 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 | 1075 | 1994 |
| 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 | 616 | 2016 |
| 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 | 586 | 1988 |
| 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 | 567 | 1989 |
| A trust region algorithm for nonlinearly constrained optimization RH Byrd, RB Schnabel, GA Shultz SIAM Journal on Numerical Analysis 24 (5), 1152-1170, 1987 | 519 | 1987 |
| 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 | 513 | 1987 |
| 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 | 504 | 1987 |
| Sample size selection in optimization methods for machine learning RH Byrd, GM Chin, J Nocedal, Y Wu Mathematical programming 134 (1), 127-155, 2012 | 470 | 2012 |
| 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 | 398 | 1985 |
| 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 | 336 | 1989 |
| 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 | 312 | 2011 |
| 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 | 261 | 1992 |
| Exact and inexact subsampled Newton methods for optimization R Bollapragada, RH Byrd, J Nocedal IMA Journal of Numerical Analysis 39 (2), 545-578, 2019 | 205 | 2019 |
| 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 | 187 | 2003 |
| 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 | 170 | 1993 |
Jorge NocedalProfessor, Industrial Engineering, Northwestern UniversityVerified email at NORTHWESTERN.EDU
