| On solving L-SR1 trust-region subproblems J Brust, JB Erway, RF Marcia Computational Optimization and Applications 66, 245-266, 2017 | 58 | 2017 |
| A dense initialization for limited-memory quasi-Newton methods J Brust, O Burdakov, JB Erway, RF Marcia Computational Optimization and Applications 74, 121-142, 2019 | 17 | 2019 |
| Large-scale quasi-Newton trust-region methods with low-dimensional linear equality constraints JJ Brust, RF Marcia, CG Petra Computational Optimization and Applications 74 (3), 669-701, 2019 | 12 | 2019 |
| Large-scale optimization with linear equality constraints using reduced compact representation JJ Brust, RF Marcia, CG Petra, MA Saunders SIAM Journal on Scientific Computing 44 (1), A103-A127, 2022 | 9 | 2022 |
| Large-scale quasi-Newton trust-region methods: High-accuracy solvers, dense initializations, and extensions JJ Brust University of California, Merced, 2018 | 9 | 2018 |
| Convergence analysis of fixed point chance constrained optimal power flow problems JJ Brust, M Anitescu IEEE Transactions on Power Systems 37 (6), 4191-4201, 2022 | 7 | 2022 |
| Computationally efficient decompositions of oblique projection matrices JJ Brust, RF Marcia, CG Petra SIAM Journal on Matrix Analysis and Applications 41 (2), 852-870, 2020 | 7 | 2020 |
| Algorithm 1030: SC-SR1: MATLAB software for limited-memory SR1 trust-region methods J Brust, O Burdakov, J Erway, R Marcia ACM Transactions on Mathematical Software 48 (4), 1-33, 2022 | 5 | 2022 |
| Compact representations of structured BFGS matrices JJ Brust, Z Di, S Leyffer, CG Petra Computational Optimization and Applications 80 (1), 55-88, 2021 | 4 | 2021 |
| Shape-changing L-SR1 trust-region methods J Brust, O Burdakov, JB Erway, RF Marcia, Y Yuan arXiv. org, 2016 | 4 | 2016 |
| Effective matrix designs for COVID-19 group testing D Brust, JJ Brust BMC bioinformatics 24 (1), 26, 2023 | 3 | 2023 |
| ALGORITHM XXX: SC-SR1: MATLAB software for solving shape-changing L-SR1 trust-region subproblems J Brust, O Burdakov, JB Erway, RF Marcia, YX Yuan arXiv preprint arXiv:1607.03533, 2016 | 3 | 2016 |
| Shape-changing trust-region methods using multipoint symmetric secant matrices JJ Brust, JB Erway, RF Marcia Optimization Methods and Software, 1-18, 2024 | 2 | 2024 |
| Nonlinear Least Squares for Large-Scale Machine Learning using Stochastic Jacobian Estimates JJ Brust ICML, Beyond first-order methods in ML systems Workshop, 2021., 2021 | 2 | 2021 |
| An Trust-Region Quasi-Newton Method JJ Brust, PE Gill arXiv preprint arXiv:2312.06884, 2023 | 1 | 2023 |
| PLSS: A Projected Linear Systems Solver JJ Brust, MA Saunders SIAM Journal on Scientific Computing 45 (2), A1012-A1037, 2023 | 1 | 2023 |
| An Trust-Region Quasi-Newton Method JJ Brust, PE Gill SIAM Journal on Scientific Computing 46 (5), A3330-A3351, 2024 | | 2024 |
| Structured Sketching for Linear Systems JJ Brust, MA Saunders arXiv preprint arXiv:2407.00746, 2024 | | 2024 |
| Useful Compact Representations for Data-Fitting JJ Brust arXiv preprint arXiv:2403.12206, 2024 | | 2024 |
| Matrix Designs for COVID-19 Group Testing JJ Brust ILAS IMAGE, 9–16, 2022 | | 2022 |
Roummel MarciaProfessor of Applied Mathematics, University of California, Merced在 ucmerced.edu 的电子邮件经过验证
