Frank E. Curtis

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Daniel P. RobinsonAssociate Professor, Lehigh UniversityVerified email at lehigh.edu
Jorge NocedalProfessor, Industrial Engineering, Northwestern UniversityVerified email at NORTHWESTERN.EDU
Andreas WaechterNorthwestern UniversityVerified email at northwestern.edu
Leon BottouFacebook AI ResearchVerified email at bottou.org
James V BurkeUniversity of WashingtonVerified email at uw.edu
Michael L. OvertonProfessor of Computer Science and Mathematics, New York UniversityVerified email at cs.nyu.edu
Richard ByrdUniversity of ColoradoVerified email at colorado.edu
Katya ScheinbergCornell UniversityVerified email at cornell.edu
Mohammadreza SamadiPhD, Industrial and Systems Engineering, Lehigh UniversityVerified email at lehigh.edu
Baoyu ZhouUniversity of ChicagoVerified email at uchicago.edu
Hao WangShanghaiTech UniversityVerified email at shanghaitech.edu.cn
Olaf SchenkProfessor, Institute of Computing, Universita della Svizzera italiana, SIAM FellowVerified email at usi.ch
Xiaocun QueLehigh UniversityVerified email at alum.lehigh.edu
Nick GouldSTFC-Rutherford Appleton LaboratoryVerified email at stfc.ac.uk
Zheng HanLehigh UniversityVerified email at lehigh.edu
Albert S. BerahasAssistant Professor, University of MichiganVerified email at umich.edu
Jiashan WangGoogleVerified email at google.com
Rui ShiPhD Candidate, Lehigh UniversityVerified email at lehigh.edu
Tim MitchellMax Planck Institute for Dynamics of Complex Technical SystemsVerified email at mpi-magdeburg.mpg.de
Travis C. JohnsonNorthwestern UniversityVerified email at traviscj.com

Frank E. Curtis

Lehigh University

Verified email at lehigh.edu - Homepage

Mathematical Optimization Scientific Computing Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Optimization methods for large-scale machine learning L Bottou, FE Curtis, J Nocedal SIAM Review 60 (2), 223-311, 2018	2971	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	177*	2016
A sequential quadratic programming algorithm for nonconvex, nonsmooth constrained optimization FE Curtis, ML Overton SIAM Journal on Optimization 22 (2), 474-500, 2012	139	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	122	2017
An inexact SQP method for equality constrained optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 19 (1), 351-369, 2008	110	2008
A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees FE Curtis, X Que Mathematical Programming Computation 7 (4), 399-428, 2015	91	2015
Infeasibility detection and SQP methods for nonlinear optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 20 (5), 2281-2299, 2010	87	2010
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	84	2020
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	78	2010
An adaptive gradient sampling algorithm for nonsmooth optimization FE Curtis, X Que Optimization Methods and Software 28 (6), 1302-1324, 2013	75	2013
An inexact Newton method for nonconvex equality constrained optimization RH Byrd, FE Curtis, J Nocedal Mathematical Programming 122 (2), 273-299, 2010	59	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	52	2017
An adaptive augmented Lagrangian method for large-scale constrained optimization FE Curtis, H Jiang, DP Robinson Mathematical Programming 152 (1-2), 201-245, 2015	49	2015
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	48	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	48	2009
Exploiting negative curvature in deterministic and stochastic optimization FE Curtis, DP Robinson Mathematical Programming 176, 69-94, 2019	45	2019
ADMM for multiaffine constrained optimization W Gao, D Goldfarb, FE Curtis Optimization Methods and Software 35 (2), 257-303, 2020	44	2020
Flexible penalty functions for nonlinear constrained optimization FE Curtis, J Nocedal IMA Journal of Numerical Analysis 28 (4), 749-769, 2008	43	2008
A self-correcting variable-metric algorithm for stochastic optimization FE Curtis Proceedings of The 33rd International Conference on Machine Learning, 632-641, 2016	42	2016
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	39	2018

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