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
Michael L. OvertonProfessor of Computer Science and Mathematics, New York UniversityVerified email at cs.nyu.edu
James V BurkeUniversity of WashingtonVerified email at uw.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
Hao WangShanghaiTech UniversityVerified email at shanghaitech.edu.cn
Olaf SchenkProfessor, Institute of Computing, Universita della Svizzera italiana, SIAM FellowVerified email at usi.ch
Xiaocun QueVerified email at alum.lehigh.edu
Baoyu ZhouLehigh UniversityVerified email at lehigh.edu
Zheng HanLehigh UniversityVerified email at lehigh.edu
Nick GouldSTFC-Rutherford Appleton LaboratoryVerified email at stfc.ac.uk
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
Albert S. BerahasAssistant Professor, University of MichiganVerified email at umich.edu
arvind raghunathanMitsubishi Electric Research LaboratoriesVerified email at merl.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	2355	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	159*	2016
A sequential quadratic programming algorithm for nonconvex, nonsmooth constrained optimization FE Curtis, ML Overton SIAM Journal on Optimization 22 (2), 474-500, 2012	125	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	100	2017
An inexact SQP method for equality constrained optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 19 (1), 351-369, 2008	98	2008
Infeasibility detection and SQP methods for nonlinear optimization RH Byrd, FE Curtis, J Nocedal SIAM Journal on Optimization 20 (5), 2281-2299, 2010	84	2010
A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees FE Curtis, X Que Mathematical Programming Computation 7 (4), 399-428, 2015	76	2015
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	69	2010
An adaptive gradient sampling algorithm for nonsmooth optimization FE Curtis, X Que Optimization Methods and Software 28 (6), 1302-1324, 2013	65	2013
An inexact Newton method for nonconvex equality constrained optimization RH Byrd, FE Curtis, J Nocedal Mathematical Programming 122 (2), 273-299, 2010	53	2010
Gradient sampling methods for nonsmooth optimization JV Burke, FE Curtis, AS Lewis, ML Overton, LEA Simões Numerical Nonsmooth Optimization, 201-225, 2020	49	2020
An adaptive augmented Lagrangian method for large-scale constrained optimization FE Curtis, H Jiang, DP Robinson Mathematical Programming 152 (1-2), 201-245, 2015	47	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	46	2015
Optimization methods for supervised machine learning: From linear models to deep learning FE Curtis, K Scheinberg Leading Developments from INFORMS Communities, 89-114, 2017	45	2017
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	45	2009
Flexible penalty functions for nonlinear constrained optimization FE Curtis, J Nocedal IMA Journal of Numerical Analysis 28 (4), 749-769, 2008	43	2008
Exploiting negative curvature in deterministic and stochastic optimization FE Curtis, DP Robinson Mathematical Programming 176 (1), 69-94, 2019	38	2019
A self-correcting variable-metric algorithm for stochastic optimization FE Curtis Proceedings of The 33rd International Conference on Machine Learning, 632-641, 2016	38	2016
An inexact sequential quadratic optimization algorithm for nonlinear optimization FE Curtis, TC Johnson, DP Robinson, A Wächter SIAM Journal on Optimization 24 (3), 1041-1074, 2014	38	2014
A sequential quadratic optimization algorithm with rapid infeasibility detection JV Burke, FE Curtis, H Wang SIAM Journal on Optimization 24 (2), 839-872, 2014	36	2014

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