A New Derivative-Free Method Using an Improved Underdetermined Quadratic Interpolation Model.
Xie, P.; and Yuan, Y.
SIAM Journal on Optimization, 35(2): 1110–1133. 2025.
Paper
doi
link
bibtex
@article{xie-yuan-2025-improved-underdetermined-model,
author = {Pengcheng Xie and Ya-xiang Yuan},
title = {A New Derivative-Free Method Using an Improved Underdetermined Quadratic Interpolation Model},
journal = {SIAM Journal on Optimization},
year = {2025},
volume = {35},
number = {2},
pages = {1110--1133},
doi = {10.1137/23M1582023},
url = {https://doi.org/10.1137/23M1582023},
keywords = {optimization}
}
Sufficient Conditions for Error Distance Reduction in the $\ell_2$-Norm Trust Region Between Minimizers of Local Nonconvex Multivariate Quadratic Approximates.
Xie, P.
Journal of Computational and Applied Mathematics, 453: 116146. 2025.
Paper
doi
link
bibtex
@article{xie-2025-distance-reduction,
author = {Pengcheng Xie},
title = {Sufficient Conditions for Error Distance Reduction in the {$\ell_2$}-Norm Trust Region Between Minimizers of Local Nonconvex Multivariate Quadratic Approximates},
journal = {Journal of Computational and Applied Mathematics},
year = {2025},
volume = {453},
pages = {116146},
doi = {10.1016/j.cam.2024.116146},
url = {https://doi.org/10.1016/j.cam.2024.116146},
keywords = {optimization}
}
An Improved Adaptive Orthogonal Basis Deflation Method for Multiple Solutions with Applications to Nonlinear Elliptic Equations in Varying Domains.
Ye, Y.; Li, L.; Xie, P.; and Yu, H.
Journal of Computational Mathematics, 44(3): 794–818. 2025.
Paper
doi
link
bibtex
@article{ye-li-xie-yu-2025-adaptive-deflation,
author = {Yangyi Ye and Lin Li and Pengcheng Xie and Haijun Yu},
title = {An Improved Adaptive Orthogonal Basis Deflation Method for Multiple Solutions with Applications to Nonlinear Elliptic Equations in Varying Domains},
journal = {Journal of Computational Mathematics},
year = {2025},
volume = {44},
number = {3},
pages = {794--818},
doi = {10.4208/jcm.2505-m2024-0276},
url = {https://doi.org/10.4208/jcm.2505-m2024-0276},
keywords = {numerical PDE}
}
Optimization Approaches for Solving Inverse Problems Under Uncertainty.
Dzahini, K. J.; Wild, S. M.; and Xie, P.
Inverse Methods for Complex Systems under Uncertainty Workshop. 2025.
Position paper, U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research
Paper
link
bibtex
@article{dzahini-wild-xie-2025-inverse-problems,
author = {Kwassi J. Dzahini and Stefan M. Wild and Pengcheng Xie},
title = {Optimization Approaches for Solving Inverse Problems Under Uncertainty},
journal = {Inverse Methods for Complex Systems under Uncertainty Workshop},
year = {2025},
note = {Position paper, U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research},
url = {https://www.orau.gov/support_files/2025InverseMethods/WildS.pdf},
keywords = {optimization}
}
A Novel Numerical Method Tailored for Unconstrained Optimization Problems.
Li, L.; Xie, P.; and Zhang, L.
2025.
Paper
link
bibtex
@misc{li-xie-zhang-2025-novel-numerical-method,
author = {Lin Li and Pengcheng Xie and Li Zhang},
title = {A Novel Numerical Method Tailored for Unconstrained Optimization Problems},
year = {2025},
eprint = {2504.02832},
archivePrefix = {arXiv},
primaryClass = {math.OC},
url = {https://arxiv.org/abs/2504.02832},
keywords = {optimization}
}
Objective Value Change and Shape-Based Accelerated Optimization for Neural Network Approximation.
Xie, P.; Zhou, Z.; and Zhou, Z.
2025.
Paper
link
bibtex
@misc{xie-zhou-zhou-2025-shape-based-optimization,
author = {Pengcheng Xie and Zihao Zhou and Zijian Zhou},
title = {Objective Value Change and Shape-Based Accelerated Optimization for Neural Network Approximation},
year = {2025},
eprint = {2508.20290},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2508.20290},
keywords = {machine learning, optimization}
}
Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy.
He, Y.; and Xie, P.
2025.
Paper
link
bibtex
@misc{he-xie-2025-model-driven-subspaces,
author = {Yitong He and Pengcheng Xie},
title = {Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy},
year = {2025},
eprint = {2509.08256},
archivePrefix = {arXiv},
primaryClass = {math.OC},
url = {https://arxiv.org/abs/2509.08256},
keywords = {optimization}
}