Frank E. Curtis

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Daniel P. RobinsonAssociate Professor, Lehigh UniversityAdresse e-mail validée de lehigh.edu
Jorge NocedalProfessor, Industrial Engineering, Northwestern UniversityAdresse e-mail validée de NORTHWESTERN.EDU
Andreas WaechterNorthwestern UniversityAdresse e-mail validée de northwestern.edu
Leon BottouFacebook AI ResearchAdresse e-mail validée de bottou.org
James V BurkeUniversity of WashingtonAdresse e-mail validée de uw.edu
Michael L. OvertonProfessor of Computer Science and Mathematics, New York UniversityAdresse e-mail validée de cs.nyu.edu
Baoyu ZhouArizona State UniversityAdresse e-mail validée de asu.edu
Mohammadreza SamadiPhD, Industrial and Systems Engineering, Lehigh UniversityAdresse e-mail validée de lehigh.edu
Katya ScheinbergGeorgia TechAdresse e-mail validée de gatech.edu
Richard ByrdUniversity of ColoradoAdresse e-mail validée de colorado.edu
Hao WangShanghaiTech UniversityAdresse e-mail validée de shanghaitech.edu.cn
Olaf SchenkProfessor, Institute of Computing, Universita della Svizzera italiana, SIAM FellowAdresse e-mail validée de usi.ch
Nick GouldSTFC-Rutherford Appleton LaboratoryAdresse e-mail validée de stfc.ac.uk
Albert S. BerahasAssistant Professor, University of MichiganAdresse e-mail validée de umich.edu
Xiaocun QuePhD, Lehigh UniversityAdresse e-mail validée de alum.lehigh.edu
Rui ShiPhD Candidate, Lehigh UniversityAdresse e-mail validée de lehigh.edu
Zheng HanLehigh UniversityAdresse e-mail validée de lehigh.edu
Jiashan WangGoogleAdresse e-mail validée de google.com
Elizabeth WongUC San DiegoAdresse e-mail validée de ucsd.edu
Daniel K. MolzahnAssistant Professor at the Georgia Institute of Technology. Computational Engineer at ArgonneAdresse e-mail validée de gatech.edu

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Frank E. Curtis

Lehigh University

Adresse e-mail validée de lehigh.edu - Page d'accueil

Mathematical Optimization Scientific Computing Machine Learning


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Optimization methods for large-scale machine learning L Bottou, FE Curtis, J Nocedal SIAM Review 60 (2), 223-311, 2018	4207	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	200*	2016
A sequential quadratic programming algorithm for nonconvex, nonsmooth constrained optimization FE Curtis, ML Overton SIAM Journal on Optimization 22 (2), 474-500, 2012	165	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	150	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	114	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	95	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	84	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	81	2017
An adaptive gradient sampling algorithm for nonsmooth optimization FE Curtis, X Que Optimization Methods and Software 28 (6), 1302-1324, 2013	81	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	69	2021
Exploiting negative curvature in deterministic and stochastic optimization FE Curtis, DP Robinson Mathematical Programming 176, 69-94, 2019	67	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	59	2015
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	55	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
ADMM for multiaffine constrained optimization W Gao, D Goldfarb, FE Curtis Optimization Methods and Software 35 (2), 257-303, 2020	54	2020
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	48	2018
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	48	2009

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