Frank E. Curtis

73 papers A* 1A 1Journal 71

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Stochastic-Gradient-Based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems. SIAM J. Optim. Frank E. Curtis, Vyacheslav Kungurtsev, Daniel P. Robinson, Qi Wang
2025	J	`jnl`	Active-Set Identification in Noisy and Stochastic Optimization. CoRR Frank E. Curtis, Daniel P. Robinson, Lara Zebiane
2025	J	`jnl`	Almost-Sure Convergence of Iterates and Multipliers in Stochastic Sequential Quadratic Optimization. J. Optim. Theory Appl. Frank E. Curtis, Xin Jiang, Qi Wang
2025	J	`jnl`	An Interior-Point Algorithm for Continuous Nonlinearly Constrained Optimization with Noisy Function and Derivative Evaluations. CoRR Frank E. Curtis, Shima Dezfulian, Andreas Wächter
2025	J	`jnl`	Fair Supervised Learning Through Constraints on Smooth Nonconvex Unfairness-Measure Surrogates. CoRR Zahra Khatti, Daniel P. Robinson, Frank E. Curtis
2025	J	`jnl`	Progressively Sampled Equality-Constrained Optimization. CoRR Frank E. Curtis, Lingjun Guo, Daniel P. Robinson
2025	J	`jnl`	Stochastic Optimization Approaches for an Operating Room and Anesthesiologist Scheduling Problem. Oper. Res. Man Yiu Tsang, Karmel S. Shehadeh, Frank E. Curtis, Beth R. Hochman, Tricia E. Brentjens
2024	J	`jnl`	A Stochastic Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Equality-Constrained Optimization. INFORMS J. Optim. Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
2024	J	`jnl`	A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear-Equality-Constrained Optimization with Rank-Deficient Jacobians. Math. Oper. Res. Albert S. Berahas, Frank E. Curtis, Michael O'Neill, Daniel P. Robinson
2024	J	`jnl`	Derivative-free bound-constrained optimization for solving structured problems with surrogate models. Optim. Methods Softw. Frank E. Curtis, Shima Dezfulian, Andreas Wächter
2024	J	`jnl`	Fair machine learning through constrained stochastic optimization and an ε-constraint method. Optim. Lett. Frank E. Curtis, Suyun Liu, Daniel P. Robinson
2024	J	`jnl`	Incremental quasi-Newton algorithms for solving a nonconvex, nonsmooth, finite-sum optimization problem. Optim. Methods Softw. Gulcin Dinc Yalcin, Frank E. Curtis
2024	J	`jnl`	Sequential Quadratic Optimization for Stochastic Optimization with Deterministic Nonlinear Inequality and Equality Constraints. SIAM J. Optim. Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
2024	J	`jnl`	Single-Loop Deterministic and Stochastic Interior-Point Algorithms for Nonlinearly Constrained Optimization. CoRR Frank E. Curtis, Xin Jiang, Qi Wang
2024	J	`jnl`	Using Synthetic Data to Mitigate Unfairness and Preserve Privacy through Single-Shot Federated Learning. CoRR Chia-Yuan Wu, Frank E. Curtis, Daniel P. Robinson
2024	J	`jnl`	Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization. Math. Program. Frank E. Curtis, Michael J. O'Neill, Daniel P. Robinson
2023	J	`jnl`	A Decomposition Algorithm with Fast Identification of Critical Contingencies for Large-Scale Security-Constrained AC-OPF. Oper. Res. Frank E. Curtis, Daniel K. Molzahn, Shenyinying Tu, Andreas Wächter, Ermin Wei, Elizabeth Wong
2023	J	`jnl`	A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems. CoRR Frank E. Curtis, Vyacheslav Kungurtsev, Daniel P. Robinson, Qi Wang
2023	A	`conf`	A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization. AISTATS Yutong Dai, Guanyi Wang, Frank E. Curtis, Daniel P. Robinson
2023	J	`jnl`	Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization. CoRR Frank E. Curtis, Xin Jiang, Qi Wang
2023	J	`jnl`	An inexact column-and-constraint generation method to solve two-stage robust optimization problems. Oper. Res. Lett. Man Yiu Tsang, Karmel S. Shehadeh, Frank E. Curtis
2023	J	`jnl`	Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition. Oper. Res. Ignacio Aravena, Daniel K. Molzahn, Shixuan Zhang, Cosmin G. Petra, Frank E. Curtis, Shenyinying Tu, Andreas Wächter, Ermin Wei, Elizabeth Wong, Amin Gholami, Kaizhao Sun, Xu Andy Sun, Stephen T. Elbert, Jesse Holzer, Arun Veeramany
2023	J	`jnl`	Worst-Case Complexity of TRACE with Inexact Subproblem Solutions for Nonconvex Smooth Optimization. SIAM J. Optim. Frank E. Curtis, Qi Wang
2022	J	`jnl`	A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer. SIAM J. Optim. Frank E. Curtis, Yutong Dai, Daniel P. Robinson
2022	J	`jnl`	A fully stochastic second-order trust region method. Optim. Methods Softw. Frank E. Curtis, Rui Shi
2022	J	`jnl`	Gradient Sampling Methods with Inexact Subproblem Solutions and Gradient Aggregation. INFORMS J. Optim. Frank E. Curtis, Minhan Li
2022	J	`jnl`	Limited-memory BFGS with displacement aggregation. Math. Program. Albert S. Berahas, Frank E. Curtis, Baoyu Zhou
2021	J	`jnl`	An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optim. Methods Softw. Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
2021	J	`jnl`	Regional complexity analysis of algorithms for nonconvex smooth optimization. Math. Program. Frank E. Curtis, Daniel P. Robinson
2021	J	`jnl`	Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. SIAM J. Optim. Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
2021	J	`jnl`	Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization. SIAM J. Optim. Frank E. Curtis, Daniel P. Robinson, Clément W. Royer, Stephen J. Wright
2020	J	`jnl`	ADMM for multiaffine constrained optimization. Optim. Methods Softw. Wenbo Gao, Donald Goldfarb, Frank E. Curtis
2020	J	`jnl`	Adaptive Stochastic Optimization. CoRR Frank E. Curtis, Katya Scheinberg
2020	J	`jnl`	Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. IEEE Signal Process. Mag. Frank E. Curtis, Katya Scheinberg
2020	J	`jnl`	Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
2020	J	`jnl`	Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. CoRR Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
2019	J	`jnl`	A Stochastic Trust Region Algorithm Based on Careful Step Normalization. INFORMS J. Optim. Frank E. Curtis, Katya Scheinberg, Rui Shi
2019	J	`jnl`	Exploiting negative curvature in deterministic and stochastic optimization. Math. Program. Frank E. Curtis, Daniel P. Robinson
2018	J	`jnl`	A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints. SIAM J. Optim. Frank E. Curtis, Andreas Wächter, Victor M. Zavala
2018	J	`jnl`	Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. SIAM J. Optim. Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
2018	J	`jnl`	Concise complexity analyses for trust region methods. Optim. Lett. Frank E. Curtis, Zachary Lubberts, Daniel P. Robinson
2018	J	`jnl`	FaRSA for ℓ1-regularized convex optimization: local convergence and numerical experience. Optim. Methods Softw. Tianyi Chen, Frank E. Curtis, Daniel P. Robinson
2018	J	`jnl`	Optimization Methods for Large-Scale Machine Learning. SIAM Rev. Léon Bottou, Frank E. Curtis, Jorge Nocedal
2017	J	`jnl`	A BFGS-SQP method for nonsmooth, nonconvex, constrained optimization and its evaluation using relative minimization profiles. Optim. Methods Softw. Frank E. Curtis, Tim Mitchell, Michael L. Overton
2017	J	`jnl`	A Reduced-Space Algorithm for Minimizing ℓ SIAM J. Optim. Tianyi Chen, Frank E. Curtis, Daniel P. Robinson
2017	J	`jnl`	A trust region algorithm with a worst-case iteration complexity of O(ϵ Math. Program. Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
2017	J	`jnl`	An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning. CoRR Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
2017	J	`jnl`	An interior-point trust-funnel algorithm for nonlinear optimization. Math. Program. Frank E. Curtis, Nicholas I. M. Gould, Daniel P. Robinson, Philippe L. Toint
2017	J	`jnl`	Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. CoRR Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
2017	J	`jnl`	Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. CoRR Frank E. Curtis, Katya Scheinberg
2017	J	`jnl`	Solving nearly-separable quadratic optimization problems as nonsmooth equations. Comput. Optim. Appl. Frank E. Curtis, Arvind U. Raghunathan
2016	A*	`conf`	A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. ICML Frank E. Curtis
2016	J	`jnl`	Adaptive augmented Lagrangian methods: algorithms and practical numerical experience. Optim. Methods Softw. Frank E. Curtis, Nicholas I. M. Gould, Hao Jiang, Daniel P. Robinson
2016	J	`jnl`	Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves. SIAM J. Optim. Frank E. Curtis, Zheng Han
2016	J	`jnl`	Optimization Methods for Large-Scale Machine Learning. CoRR Léon Bottou, Frank E. Curtis, Jorge Nocedal
2015	J	`jnl`	A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization. Comput. Optim. Appl. Frank E. Curtis, Zheng Han, Daniel P. Robinson
2015	J	`jnl`	A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees. Math. Program. Comput. Frank E. Curtis, Xiaocun Que
2015	J	`jnl`	An adaptive augmented Lagrangian method for large-scale constrained optimization. Math. Program. Frank E. Curtis, Hao Jiang, Daniel P. Robinson
2015	J	`jnl`	Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
2015	J	`jnl`	Primal-Dual Active-Set Methods for Isotonic Regression and Trend Filtering. CoRR Zheng Han, Frank E. Curtis
2014	J	`jnl`	A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. SIAM J. Optim. James V. Burke, Frank E. Curtis, Hao Wang
2014	J	`jnl`	An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization. SIAM J. Optim. Frank E. Curtis, Travis C. Johnson, Daniel P. Robinson, Andreas Wächter
2013	J	`jnl`	An adaptive gradient sampling algorithm for non-smooth optimization. Optim. Methods Softw. Frank E. Curtis, Xiaocun Que
2012	J	`jnl`	A Sequential Quadratic Programming Algorithm for Nonconvex, Nonsmooth Constrained Optimization. SIAM J. Optim. Frank E. Curtis, Michael L. Overton
2012	J	`jnl`	A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations. Math. Program. Frank E. Curtis, Johannes Huber, Olaf Schenk, Andreas Wächter
2012	J	`jnl`	A penalty-interior-point algorithm for nonlinear constrained optimization. Math. Program. Comput. Frank E. Curtis
2010	J	`jnl`	An Interior-Point Algorithm for Large-Scale Nonlinear Optimization with Inexact Step Computations. SIAM J. Sci. Comput. Frank E. Curtis, Olaf Schenk, Andreas Wächter
2010	J	`jnl`	An inexact Newton method for nonconvex equality constrained optimization. Math. Program. Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
2010	J	`jnl`	Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
2009	J	`jnl`	A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. Frank E. Curtis, Jorge Nocedal, Andreas Wächter
2008	J	`jnl`	An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
2007	J	`jnl`	Steplength selection in interior-point methods for quadratic programming. Appl. Math. Lett. Frank E. Curtis, Jorge Nocedal
2004	J	`jnl`	Central groupoids, central digraphs, and zero-one matrices A satisfying A J. Comb. Theory A Frank E. Curtis, John Drew, Chi-Kwong Li, Daniel Pragel