受强制性开放获取政策约束的文章 - Frank E. Curtis了解详情
可在其他位置公开访问的文章：35 篇
Optimization methods for large-scale machine learning
L Bottou, FE Curtis, J Nocedal
SIAM Review 60 (2), 223-311, 2018
强制性开放获取政策： US National Science Foundation, US Department of Energy, US Department of …
A BFGS-SQP Method for Nonsmooth, Nonconvex, Constrained Optimization and its Evaluation using Relative Minimization Profiles
FE Curtis, T Mitchell, ML Overton
Optimization Methods and Software 31 (1), 148-181, 2017
强制性开放获取政策： US National Science Foundation, US Department of Energy
Gradient sampling methods for nonsmooth optimization
JV Burke, FE Curtis, AS Lewis, ML Overton, LEA Simões
Numerical nonsmooth optimization: State of the art algorithms, 201-225, 2020
强制性开放获取政策： US National Science Foundation, US Department of Energy
Optimization methods for supervised machine learning: From linear models to deep learning
FE Curtis, K Scheinberg
Leading developments from INFORMS communities, 89-114, 2017
强制性开放获取政策： US National Science Foundation, US Department of Energy
Sequential quadratic optimization for nonlinear equality constrained stochastic optimization
AS Berahas, FE Curtis, D Robinson, B Zhou
SIAM Journal on Optimization 31 (2), 1352-1379, 2021
强制性开放获取政策： US National Science Foundation
Exploiting negative curvature in deterministic and stochastic optimization
FE Curtis, DP Robinson
Mathematical Programming 176, 69-94, 2019
强制性开放获取政策： US National Science Foundation, US Department of Energy
An adaptive augmented Lagrangian method for large-scale constrained optimization
FE Curtis, H Jiang, DP Robinson
Mathematical Programming 152 (1-2), 201-245, 2015
强制性开放获取政策： US Department of Energy
ADMM for multiaffine constrained optimization
W Gao, D Goldfarb, FE Curtis
Optimization Methods and Software 35 (2), 257-303, 2020
强制性开放获取政策： US National Science Foundation, US Department of Energy
A stochastic trust region algorithm based on careful step normalization
FE Curtis, K Scheinberg, R Shi
Informs Journal on Optimization 1 (3), 200-220, 2019
强制性开放获取政策： US National Science Foundation, US Department of Energy
A sequential algorithm for solving nonlinear optimization problems with chance constraints
FE Curtis, A Wächter, VM Zavala
SIAM Journal on Optimization 28 (1), 930–958, 2018
强制性开放获取政策： US National Science Foundation, US Department of Energy
Trust-region Newton-CG with strong second-order complexity guarantees for nonconvex optimization
FE Curtis, DP Robinson, CW Royer, SJ Wright
SIAM Journal on Optimization 31 (1), 518-544, 2021
强制性开放获取政策： US National Science Foundation, US Department of Energy, US Department of …
Complexity analysis of a trust funnel algorithm for equality constrained optimization
FE Curtis, DP Robinson, M Samadi
Lehigh University ISE/COR@L, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy
Adaptive stochastic optimization: A framework for analyzing stochastic optimization algorithms
FE Curtis, K Scheinberg
IEEE Signal Processing Magazine 37 (5), 32-42, 2020
强制性开放获取政策： US National Science Foundation
Recent developments in security-constrained AC optimal power flow: Overview of challenge 1 in the ARPA-E grid optimization competition
I Aravena, DK Molzahn, S Zhang, CG Petra, FE Curtis, S Tu, A Wächter, ...
Operations research 71 (6), 1997-2014, 2023
强制性开放获取政策： US National Science Foundation, US Department of Energy
A reduced-space algorithm for minimizing -regularized convex functions
T Chen, FE Curtis, DP Robinson
SIAM Journal on Optimization 27 (3), 1583-1610, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy
Adaptive augmented Lagrangian methods: Algorithms and practical numerical experience
FE Curtis, NIM Gould, H Jiang, DP Robinson
Optimization Methods and Software 31 (1), 157-186, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy, UK Engineering and …
Handling nonpositive curvature in a limited memory steepest descent method
FE Curtis, W Guo
IMA Journal of Numerical Analysis 36 (2), 717-742, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy
Iterative reweighted linear least squares for exact penalty subproblems on product sets
JV Burke, FE Curtis, H Wang, J Wang
SIAM Journal on Optimization 25 (1), 261-294, 2015
强制性开放获取政策： US Department of Energy
A fully stochastic second-order trust region method
FE Curtis, R Shi
Optimization Methods and Software 37 (3), 844-877, 2022
强制性开放获取政策： US National Science Foundation, US Department of Energy
R-Linear Convergence of Limited Memory Steepest Descent
FE Curtis, W Guo
Technical Report 16T-010, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy
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