Frank E. Curtis

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 46

Top Topics

Globally Convergent

Augmented Lagrangian

Optimization Method

Quadratic Optimization

Top Venues

Optim. Methods Softw.

Publications

Gulcin Dinc Yalcin, Frank E. Curtis
Incremental quasi-Newton algorithms for solving a nonconvex, nonsmooth, finite-sum optimization problem. Optim. Methods Softw. 39 (2) (2024)
Frank E. Curtis, Michael O'Neill, Daniel P. Robinson
Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization. Math. Program. 205 (1) (2024)
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
Recent Developments in Security-Constrained AC Optimal Power Flow: Overview of Challenge 1 in the ARPA-E Grid Optimization Competition. Oper. Res. 71 (6) (2023)
Frank E. Curtis, Xin Jiang, Qi Wang
Almost-sure convergence of iterates and multipliers in stochastic sequential quadratic optimization. CoRR (2023)
Man Yiu Tsang, Karmel S. Shehadeh, Frank E. Curtis
An inexact column-and-constraint generation method to solve two-stage robust optimization problems. Oper. Res. Lett. 51 (1) (2023)
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) (2023)
Frank E. Curtis, Qi Wang
Worst-Case Complexity of TRACE with Inexact Subproblem Solutions for Nonconvex Smooth Optimization. SIAM J. Optim. 33 (3) (2023)
Frank E. Curtis, Vyacheslav Kungurtsev, Daniel P. Robinson, Qi Wang
A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems. CoRR (2023)
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)
Albert S. Berahas, Frank E. Curtis, Baoyu Zhou
Limited-memory BFGS with displacement aggregation. Math. Program. 194 (1) (2022)
Frank E. Curtis, Rui Shi
A fully stochastic second-order trust region method. Optim. Methods Softw. 37 (3) (2022)
Frank E. Curtis, Minhan Li
Gradient Sampling Methods with Inexact Subproblem Solutions and Gradient Aggregation. INFORMS J. Optim. 4 (4) (2022)
Frank E. Curtis, Yutong Dai, Daniel P. Robinson
A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer. SIAM J. Optim. 32 (2) (2022)
Frank E. Curtis, Daniel P. Robinson
Regional complexity analysis of algorithms for nonconvex smooth optimization. Math. Program. 187 (1) (2021)
Frank E. Curtis, Daniel P. Robinson, Clément W. Royer, Stephen J. Wright
Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization. SIAM J. Optim. 31 (1) (2021)
Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optim. Methods Softw. 36 (1) (2021)
Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. SIAM J. Optim. 31 (2) (2021)
Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. CoRR (2020)
Frank E. Curtis, Katya Scheinberg
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. IEEE Signal Process. Mag. 37 (5) (2020)
Wenbo Gao, Donald Goldfarb, Frank E. Curtis
ADMM for multiaffine constrained optimization. Optim. Methods Softw. 35 (2) (2020)
Frank E. Curtis, Katya Scheinberg
Adaptive Stochastic Optimization. CoRR (2020)
James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
Inexact Sequential Quadratic Optimization with Penalty Parameter Updates within the QP Solver. SIAM J. Optim. 30 (3) (2020)
Frank E. Curtis, Katya Scheinberg, Rui Shi
A Stochastic Trust Region Algorithm Based on Careful Step Normalization. INFORMS J. Optim. 1 (3) (2019)
Frank E. Curtis, Daniel P. Robinson
Exploiting negative curvature in deterministic and stochastic optimization. Math. Program. 176 (1-2) (2019)
Léon Bottou, Frank E. Curtis, Jorge Nocedal
Optimization Methods for Large-Scale Machine Learning. SIAM Rev. 60 (2) (2018)
Frank E. Curtis, Andreas Wächter, Victor M. Zavala
A Sequential Algorithm for Solving Nonlinear Optimization Problems with Chance Constraints. SIAM J. Optim. 28 (1) (2018)
Frank E. Curtis, Zachary Lubberts, Daniel P. Robinson
Concise complexity analyses for trust region methods. Optim. Lett. 12 (8) (2018)
Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. SIAM J. Optim. 28 (2) (2018)
Tianyi Chen, Frank E. Curtis, Daniel P. Robinson
FaRSA for ℓ1-regularized convex optimization: local convergence and numerical experience. Optim. Methods Softw. 33 (2) (2018)
Frank E. Curtis, Tim Mitchell, Michael L. Overton
A BFGS-SQP method for nonsmooth, nonconvex, constrained optimization and its evaluation using relative minimization profiles. Optim. Methods Softw. 32 (1) (2017)
Frank E. Curtis, Katya Scheinberg
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning. CoRR (2017)
Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
An Accelerated Communication-Efficient Primal-Dual Optimization Framework for Structured Machine Learning. CoRR (2017)
Frank E. Curtis, Arvind U. Raghunathan
Solving nearly-separable quadratic optimization problems as nonsmooth equations. Comput. Optim. Appl. 67 (2) (2017)
Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. CoRR (2017)
Tianyi Chen, Frank E. Curtis, Daniel P. Robinson
-Regularized Convex Functions. SIAM J. Optim. 27 (3) (2017)
Frank E. Curtis, Daniel P. Robinson, Mohammadreza Samadi
) for nonconvex optimization. Math. Program. 162 (1-2) (2017)
Frank E. Curtis, Nicholas I. M. Gould, Daniel P. Robinson, Philippe L. Toint
An interior-point trust-funnel algorithm for nonlinear optimization. Math. Program. 161 (1-2) (2017)
Frank E. Curtis, Nicholas I. M. Gould, Hao Jiang, Daniel P. Robinson
Adaptive augmented Lagrangian methods: algorithms and practical numerical experience. Optim. Methods Softw. 31 (1) (2016)
Léon Bottou, Frank E. Curtis, Jorge Nocedal
Optimization Methods for Large-Scale Machine Learning. CoRR (2016)
Frank E. Curtis, Zheng Han
Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves. SIAM J. Optim. 26 (4) (2016)
Frank E. Curtis
A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization. ICML (2016)
James V. Burke, Frank E. Curtis, Hao Wang, Jiashan Wang
Iterative Reweighted Linear Least Squares for Exact Penalty Subproblems on Product Sets. SIAM J. Optim. 25 (1) (2015)
Frank E. Curtis, Hao Jiang, Daniel P. Robinson
An adaptive augmented Lagrangian method for large-scale constrained optimization. Math. Program. 152 (1-2) (2015)
Zheng Han, Frank E. Curtis
Primal-Dual Active-Set Methods for Isotonic Regression and Trend Filtering. CoRR (2015)
Frank E. Curtis, Zheng Han, Daniel P. Robinson
A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization. Comput. Optim. Appl. 60 (2) (2015)
Frank E. Curtis, Xiaocun Que
A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees. Math. Program. Comput. 7 (4) (2015)
Frank E. Curtis, Travis C. Johnson, Daniel P. Robinson, Andreas Wächter
An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization. SIAM J. Optim. 24 (3) (2014)
James V. Burke, Frank E. Curtis, Hao Wang
A Sequential Quadratic Optimization Algorithm with Rapid Infeasibility Detection. SIAM J. Optim. 24 (2) (2014)
Frank E. Curtis, Xiaocun Que
An adaptive gradient sampling algorithm for non-smooth optimization. Optim. Methods Softw. 28 (6) (2013)
Frank E. Curtis, Johannes Huber, Olaf Schenk, Andreas Wächter
A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations. Math. Program. 136 (1) (2012)
Frank E. Curtis
A penalty-interior-point algorithm for nonlinear constrained optimization. Math. Program. Comput. 4 (2) (2012)
Frank E. Curtis, Michael L. Overton
A Sequential Quadratic Programming Algorithm for Nonconvex, Nonsmooth Constrained Optimization. SIAM J. Optim. 22 (2) (2012)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. 20 (5) (2010)
Frank E. Curtis, Olaf Schenk, Andreas Wächter
An Interior-Point Algorithm for Large-Scale Nonlinear Optimization with Inexact Step Computations. SIAM J. Sci. Comput. 32 (6) (2010)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
An inexact Newton method for nonconvex equality constrained optimization. Math. Program. 122 (2) (2010)
Frank E. Curtis, Jorge Nocedal, Andreas Wächter
A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. 20 (3) (2009)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. 19 (1) (2008)
Frank E. Curtis, Jorge Nocedal
Steplength selection in interior-point methods for quadratic programming. Appl. Math. Lett. 20 (5) (2007)
Frank E. Curtis, John Drew, Chi-Kwong Li, Daniel Pragel
=J . J. Comb. Theory, Ser. A 105 (1) (2004)