| Numerical Optimization, Second Edition J Nocedal, SJ Wright Numerical optimization, 497-528, 2006 | 42323* | 2006 |
| On the limited memory BFGS method for large scale optimization DC Liu, J Nocedal Mathematical programming 45 (1), 503-528, 1989 | 9542 | 1989 |
| 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 | 7292 | 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 | 3948 | 1997 |
| Updating quasi-Newton matrices with limited storage J Nocedal Mathematics of computation 35 (151), 773-782, 1980 | 3728 | 1980 |
| Optimization methods for large-scale machine learning L Bottou, FE Curtis, J Nocedal SIAM review 60 (2), 223-311, 2018 | 3724 | 2018 |
| On large-batch training for deep learning: Generalization gap and sharp minima NS Keskar, D Mudigere, J Nocedal, M Smelyanskiy, PTP Tang arXiv preprint arXiv:1609.04836, 2016 | 3466 | 2016 |
| An interior point algorithm for large-scale nonlinear programming RH Byrd, ME Hribar, J Nocedal SIAM Journal on Optimization 9 (4), 877-900, 1999 | 2276 | 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 | 2105 | 2000 |
| Numerical optimization SJ Wright | 2050 | 2006 |
| Global convergence properties of conjugate gradient methods for optimization JC Gilbert, J Nocedal SIAM Journal on optimization 2 (1), 21-42, 1992 | 1510 | 1992 |
| Knitro: An Integrated Package for Nonlinear Optimization RH Byrd, J Nocedal, RA Waltz Large-scale nonlinear optimization, 35-59, 2006 | 1418 | 2006 |
| An interior algorithm for nonlinear optimization that combines line search and trust region steps RA Waltz, JL Morales, J Nocedal, D Orban Mathematical programming 107 (3), 391-408, 2006 | 1302 | 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 | 1038 | 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 | 572 | 2016 |
| 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 | 556 | 1989 |
| Theory of algorithms for unconstrained optimization J Nocedal Acta numerica 1, 199-242, 1992 | 518 | 1992 |
| Remark on “Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization” JL Morales, J Nocedal ACM Transactions on Mathematical Software (TOMS) 38 (1), 1-4, 2011 | 497 | 2011 |
| 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 | 497 | 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 | 443 | 2012 |
Richard ByrdUniversity of Colorado在 colorado.edu 的电子邮件经过验证
