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Frank E. Curtis
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- affiliation: Lehigh University, Department of Industrial and Systems Engineering, Bethlehem, PA, USA
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2020 – today
- 2024
- [j48]Frank E. Curtis
, Michael O'Neill
Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization. Math. Program. 205(1): 431-483 (2024) - [j47]Gulcin Dinc Yalcin
Incremental quasi-Newton algorithms for solving a nonconvex, nonsmooth, finite-sum optimization problem. Optim. Methods Softw. 39(2): 345-367 (2024) - [i10]Frank E. Curtis, Xin Jiang, Qi Wang:
Single-Loop Deterministic and Stochastic Interior-Point Algorithms for Nonlinearly Constrained Optimization. CoRR abs/2408.16186 (2024) - 2023
- [j46]Ignacio Aravena, Daniel K. Molzahn, Shixuan Zhang
Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition. Oper. Res. 71(6): 1997-2014 (2023) - [j45]Frank E. Curtis, Daniel K. Molzahn, Shenyinying Tu, Andreas Wächter, Ermin Wei, Elizabeth Wong
A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF. Oper. Res. 71(6): 2031-2044 (2023) - [j44]Man Yiu Tsang
An inexact column-and-constraint generation method to solve two-stage robust optimization problems. Oper. Res. Lett. 51(1): 92-98 (2023) - [j43]Frank E. Curtis
Worst-Case Complexity of TRACE with Inexact Subproblem Solutions for Nonconvex Smooth Optimization. SIAM J. Optim. 33(3): 2191-2221 (2023) - [c2]Yutong Dai, Guanyi Wang, Frank E. Curtis, Daniel P. Robinson:
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization. AISTATS 2023: 5107-5133 - [i9]Frank E. Curtis, Vyacheslav Kungurtsev
A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems. CoRR abs/2304.14907 (2023) - [i8]Frank E. Curtis, Xin Jiang, Qi Wang:
Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization. CoRR abs/2308.03687 (2023) - 2022
- [j42]Frank E. Curtis
Gradient Sampling Methods with Inexact Subproblem Solutions and Gradient Aggregation. INFORMS J. Optim. 4(4): 426-445 (2022) - [j41]Albert S. Berahas
Limited-memory BFGS with displacement aggregation. Math. Program. 194(1): 121-157 (2022) - [j40]Frank E. Curtis
A fully stochastic second-order trust region method. Optim. Methods Softw. 37(3): 844-877 (2022) - [j39]Frank E. Curtis
A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer. SIAM J. Optim. 32(2): 545-572 (2022) - 2021
- [j38]Frank E. Curtis
Regional complexity analysis of algorithms for nonconvex smooth optimization. Math. Program. 187(1): 579-615 (2021) - [j37]Chenxin Ma
An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optim. Methods Softw. 36(1): 20-44 (2021) - [j36]Frank E. Curtis
Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization. SIAM J. Optim. 31(1): 518-544 (2021) - [j35]Albert S. Berahas
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. SIAM J. Optim. 31(2): 1352-1379 (2021) - 2020
- [j34]Wenbo Gao, Donald Goldfarb, Frank E. Curtis
ADMM for multiaffine constrained optimization. Optim. Methods Softw. 35(2): 257-303 (2020) - [j33]James V. Burke, Frank E. Curtis
Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. SIAM J. Optim. 30(3): 1822-1849 (2020) - [j32]Frank E. Curtis
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. IEEE Signal Process. Mag. 37(5): 32-42 (2020) - [i7]Frank E. Curtis
Adaptive Stochastic Optimization. CoRR abs/2001.06699 (2020) - [i6]Albert S. Berahas, Frank E. Curtis
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. CoRR abs/2007.10525 (2020)
2010 – 2019
- 2019
- [j31]Frank E. Curtis
A Stochastic Trust Region Algorithm Based on Careful Step Normalization. INFORMS J. Optim. 1(3): 200-220 (2019) - [j30]Frank E. Curtis
Exploiting negative curvature in deterministic and stochastic optimization. Math. Program. 176(1-2): 69-94 (2019) - 2018
- [j29]Frank E. Curtis
Concise complexity analyses for trust region methods. Optim. Lett. 12(8): 1713-1724 (2018) - [j28]Tianyi Chen
FaRSA for ℓ1-regularized convex optimization: local convergence and numerical experience. Optim. Methods Softw. 33(2): 396-415 (2018) - [j27]Frank E. Curtis
A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints. SIAM J. Optim. 28(1): 930-958 (2018) - [j26]Frank E. Curtis
Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. SIAM J. Optim. 28(2): 1533-1563 (2018) - [j25]Léon Bottou, Frank E. Curtis
Optimization Methods for Large-Scale Machine Learning. SIAM Rev. 60(2): 223-311 (2018) - 2017
- [j24]Frank E. Curtis
Solving nearly-separable quadratic optimization problems as nonsmooth equations. Comput. Optim. Appl. 67(2): 317-360 (2017) - [j23]Frank E. Curtis
An interior-point trust-funnel algorithm for nonlinear optimization. Math. Program. 161(1-2): 73-134 (2017) - [j22]Frank E. Curtis
A trust region algorithm with a worst-case iteration complexity of O(ϵ -3/2) for nonconvex optimization. Math. Program. 162(1-2): 1-32 (2017) - [j21]Frank E. Curtis
A BFGS-SQP method for nonsmooth, nonconvex, constrained optimization and its evaluation using relative minimization profiles. Optim. Methods Softw. 32(1): 148-181 (2017) - [j20]Tianyi Chen
A Reduced-Space Algorithm for Minimizing ℓ1-Regularized Convex Functions. SIAM J. Optim. 27(3): 1583-1610 (2017) - [i5]Frank E. Curtis, Katya Scheinberg:
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. CoRR abs/1706.10207 (2017) - [i4]Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi:
Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. CoRR abs/1707.00337 (2017) - [i3]Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác:
An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning. CoRR abs/1711.05305 (2017) - 2016
- [j19]Frank E. Curtis
Adaptive augmented Lagrangian methods: algorithms and practical numerical experience. Optim. Methods Softw. 31(1): 157-186 (2016) - [j18]Frank E. Curtis
Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves. SIAM J. Optim. 26(4): 2261-2283 (2016) - [c1]Frank E. Curtis:
A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. ICML 2016: 632-641 - [i2]Léon Bottou, Frank E. Curtis, Jorge Nocedal:
Optimization Methods for Large-Scale Machine Learning. CoRR abs/1606.04838 (2016) - 2015
- [j17]Frank E. Curtis
A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization. Comput. Optim. Appl. 60(2): 311-341 (2015) - [j16]Frank E. Curtis
An adaptive augmented Lagrangian method for large-scale constrained optimization. Math. Program. 152(1-2): 201-245 (2015) - [j15]Frank E. Curtis
A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees. Math. Program. Comput. 7(4): 399-428 (2015) - [j14]James V. Burke, Frank E. Curtis
Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. SIAM J. Optim. 25(1): 261-294 (2015) - [i1]Zheng Han, Frank E. Curtis
Primal-Dual Active-Set Methods for Isotonic Regression and Trend Filtering. CoRR abs/1508.02452 (2015) - 2014
- [j13]James V. Burke, Frank E. Curtis
A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. SIAM J. Optim. 24(2): 839-872 (2014) - [j12]Frank E. Curtis
An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization. SIAM J. Optim. 24(3): 1041-1074 (2014) - 2013
- [j11]Frank E. Curtis
An adaptive gradient sampling algorithm for non-smooth optimization. Optim. Methods Softw. 28(6): 1302-1324 (2013) - 2012
- [j10]Frank E. Curtis
A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations. Math. Program. 136(1): 209-227 (2012) - [j9]Frank E. Curtis
A penalty-interior-point algorithm for nonlinear constrained optimization. Math. Program. Comput. 4(2): 181-209 (2012) - [j8]Frank E. Curtis
A Sequential Quadratic Programming Algorithm for Nonconvex, Nonsmooth Constrained Optimization. SIAM J. Optim. 22(2): 474-500 (2012) - 2010
- [j7]Richard H. Byrd, Frank E. Curtis
An inexact Newton method for nonconvex equality constrained optimization. Math. Program. 122(2): 273-299 (2010) - [j6]Richard H. Byrd, Frank E. Curtis
Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. 20(5): 2281-2299 (2010) - [j5]Frank E. Curtis
An Interior-Point Algorithm for Large-Scale Nonlinear Optimization with Inexact Step Computations. SIAM J. Sci. Comput. 32(6): 3447-3475 (2010)
2000 – 2009
- 2009
- [j4]Frank E. Curtis
A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. 20(3): 1224-1249 (2009) - 2008
- [j3]Richard H. Byrd, Frank E. Curtis
An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. 19(1): 351-369 (2008) - 2007
- [j2]Frank E. Curtis, Jorge Nocedal:
Steplength selection in interior-point methods for quadratic programming. Appl. Math. Lett. 20(5): 516-523 (2007) - 2004
- [j1]Frank E. Curtis
Central groupoids, central digraphs, and zero-one matrices A satisfying A2=J . J. Comb. Theory A 105(1): 35-50 (2004)
Coauthor Index
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last updated on 2024-09-30 00:07 CEST by the dblp team
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