Frank E. Curtis

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Daniel P. RobinsonAssociate Professor, Lehigh UniversityEmail yang diverifikasi di lehigh.edu
Jorge NocedalProfessor, Industrial Engineering, Northwestern UniversityEmail yang diverifikasi di NORTHWESTERN.EDU
Andreas WaechterNorthwestern UniversityEmail yang diverifikasi di northwestern.edu
Leon BottouFacebook AI ResearchEmail yang diverifikasi di bottou.org
James V BurkeUniversity of WashingtonEmail yang diverifikasi di uw.edu
Michael L. OvertonProfessor of Computer Science and Mathematics, New York UniversityEmail yang diverifikasi di cs.nyu.edu
Baoyu ZhouArizona State UniversityEmail yang diverifikasi di asu.edu
Mohammadreza SamadiPhD, Industrial and Systems Engineering, Lehigh UniversityEmail yang diverifikasi di lehigh.edu
Katya ScheinbergGeorgia TechEmail yang diverifikasi di gatech.edu
Richard ByrdUniversity of ColoradoEmail yang diverifikasi di colorado.edu
Hao WangShanghaiTech UniversityEmail yang diverifikasi di shanghaitech.edu.cn
Olaf SchenkProfessor, Institute of Computing, Universita della Svizzera italiana, SIAM FellowEmail yang diverifikasi di usi.ch
Albert S. BerahasAssistant Professor, University of MichiganEmail yang diverifikasi di umich.edu
Nick GouldSTFC-Rutherford Appleton LaboratoryEmail yang diverifikasi di stfc.ac.uk
Xiaocun QuePhD, Lehigh UniversityEmail yang diverifikasi di alum.lehigh.edu
Rui ShiPhD Candidate, Lehigh UniversityEmail yang diverifikasi di lehigh.edu
Zheng HanLehigh UniversityEmail yang diverifikasi di lehigh.edu
Elizabeth WongUC San DiegoEmail yang diverifikasi di ucsd.edu
Daniel K. MolzahnAssistant Professor at the Georgia Institute of Technology. Computational Engineer at ArgonneEmail yang diverifikasi di gatech.edu
Ermin WeiNorthwestern UniversityEmail yang diverifikasi di northwestern.edu

Ikuti

Frank E. Curtis

Lehigh University

Email yang diverifikasi di lehigh.edu - Beranda

Mathematical Optimization Scientific Computing Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Optimization methods for large-scale machine learning L Bottou, FE Curtis, J Nocedal SIAM Review 60 (2), 223-311, 2018	4304	2018
A trust region algorithm with a worst-case iteration complexity of for nonconvex optimization FE Curtis, DP Robinson, M Samadi Mathematical Programming, 1-32, 2016	208*	2016
A sequential quadratic programming algorithm for nonconvex, nonsmooth constrained optimization FE Curtis, ML Overton SIAM Journal on Optimization 22 (2), 474-500, 2012	167	2012
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	151	2017
An inexact SQP method for equality constrained optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 19 (1), 351-369, 2008	117	2008
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	115	2020
A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees FE Curtis, X Que Mathematical Programming Computation 7 (4), 399-428, 2015	114	2015
Infeasibility detection and SQP methods for nonlinear optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 20 (5), 2281-2299, 2010	98	2010
An interior-point algorithm for large-scale nonlinear optimization with inexact step computations FE Curtis, O Schenk, A Wächter SIAM Journal on Scientific Computing 32 (6), 3447-3475, 2010	87	2010
Optimization methods for supervised machine learning: From linear models to deep learning FE Curtis, K Scheinberg Leading developments from INFORMS communities, 89-114, 2017	83	2017
An adaptive gradient sampling algorithm for nonsmooth optimization FE Curtis, X Que Optimization Methods and Software 28 (6), 1302-1324, 2013	82	2013
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	73	2021
Exploiting negative curvature in deterministic and stochastic optimization FE Curtis, DP Robinson Mathematical Programming 176, 69-94, 2019	68	2019
An inexact Newton method for nonconvex equality constrained optimization RH Byrd, FE Curtis, J Nocedal Mathematical Programming 122 (2), 273-299, 2010	63	2010
An adaptive augmented Lagrangian method for large-scale constrained optimization FE Curtis, H Jiang, DP Robinson Mathematical Programming 152 (1-2), 201-245, 2015	60	2015
ADMM for multiaffine constrained optimization W Gao, D Goldfarb, FE Curtis Optimization Methods and Software 35 (2), 257-303, 2020	57	2020
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	57	2019
A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization FE Curtis, Z Han, DP Robinson Computational Optimization and Applications 60 (2), 311-341, 2015	55	2015
A matrix-free algorithm for equality constrained optimization problems with rank-deficient Jacobians FE Curtis, J Nocedal, A Wächter SIAM Journal on Optimization 20 (3), 1224-1249, 2009	50	2009
Flexible penalty functions for nonlinear constrained optimization FE Curtis, J Nocedal IMA Journal of Numerical Analysis 28 (4), 749-769, 2008	49	2008

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