On solving trust-region and other regularised subproblems in optimization. - Nicholas I. M. Gould; Daniel P. Robinson; H. Sue Thorne (Math. Program. Comput., 2010)

A Second Derivative SQP Method: Global Convergence. - Nicholas I. M. Gould; Daniel P. Robinson (SIAM J. Optim., 2010)

A Second Derivative SQP Method: Local Convergence and Practical Issues. - Nicholas I. M. Gould; Daniel P. Robinson (SIAM J. Optim., 2010)

A primal-dual augmented Lagrangian. - Philip E. Gill; Daniel P. Robinson (Comput. Optim. Appl., 2012)

Trajectory-following methods for large-scale degenerate convex quadratic programming. - Nicholas I. M. Gould; Dominique Orban; Daniel P. Robinson (Math. Program. Comput., 2013)

A Globally Convergent Stabilized SQP Method. - Philip E. Gill; Daniel P. Robinson (SIAM J. Optim., 2013)

Subspace Accelerated Matrix Splitting Algorithms for Asymmetric and Symmetric Linear Complementarity Problems. - Daniel P. Robinson; Liming Feng; Jorge Nocedal; Jong-Shi Pang (SIAM J. Optim., 2013)

An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization. - Frank E. Curtis; Travis C. Johnson; Daniel P. Robinson; Andreas Wächter (SIAM J. Optim., 2014)

A Filter Method with Unified Step Computation for Nonlinear Optimization. - Nicholas I. M. Gould; Yueling Loh; Daniel P. Robinson (SIAM J. Optim., 2014)

Sparse Subspace Clustering with Missing Entries. - Congyuan Yang; Daniel P. Robinson; René Vidal (ICML, 2015)

A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization. - Frank E. Curtis; Zheng Han; Daniel P. Robinson (Comput. Optim. Appl., 2015)

Primal-Dual Active-Set Methods for Large-Scale Optimization. - Daniel P. Robinson (J. Optim. Theory Appl., 2015)

An adaptive augmented Lagrangian method for large-scale constrained optimization. - Frank E. Curtis; Hao Jiang; Daniel P. Robinson (Math. Program., 2015)

A Nonmonotone Filter SQP Method: Local Convergence and Numerical Results. - Nicholas I. M. Gould; Yueling Loh; Daniel P. Robinson (SIAM J. Optim., 2015)

A Solver for Nonconvex Bound-Constrained Quadratic Optimization. - Hassan Mohy-ud-Din; Daniel P. Robinson (SIAM J. Optim., 2015)

A divide-and-conquer framework for large-scale subspace clustering. - Chong You; Claire Donnat; Daniel P. Robinson; René Vidal (ACSSC, 2016)

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. - Chong You; Chun-Guang Li; Daniel P. Robinson; René Vidal (CVPR, 2016)

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. - Chong You; Daniel P. Robinson; René Vidal (CVPR, 2016)

Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. - Daniel P. Robinson; Suchi Saria (IJCAI, 2016)

Adaptive augmented Lagrangian methods: algorithms and practical numerical experience. - Frank E. Curtis; Nicholas I. M. Gould; Hao Jiang; Daniel P. Robinson (Optim. Methods Softw., 2016)

Provable Self-Representation Based Outlier Detection in a Union of Subspaces. - Chong You; Daniel P. Robinson; René Vidal (CVPR, 2017)

A dual gradient-projection method for large-scale strictly convex quadratic problems. - Nicholas I. M. Gould; Daniel P. Robinson (Comput. Optim. Appl., 2017)

A Flexible ADMM Algorithm for Big Data Applications. - Daniel P. Robinson; Rachael Tappenden (J. Sci. Comput., 2017)

An interior-point trust-funnel algorithm for nonlinear optimization. - Frank E. Curtis; Nicholas I. M. Gould; Daniel P. Robinson; Philippe L. Toint (Math. Program., 2017)

A trust region algorithm with a worst-case iteration complexity of O(ϵ -3/2) for nonconvex optimization. - Frank E. Curtis; Daniel P. Robinson; Mohammadreza Samadi (Math. Program., 2017)

A stabilized SQP method: superlinear convergence. - Philip E. Gill; Vyacheslav Kungurtsev; Daniel P. Robinson (Math. Program., 2017)

A Reduced-Space Algorithm for Minimizing ℓ1-Regularized Convex Functions. - Tianyi Chen; Frank E. Curtis; Daniel P. Robinson (SIAM J. Optim., 2017)

Sparse Recovery over Graph Incidence Matrices. - Mengnan Zhao; M. Devrim Kaba; René Vidal; Daniel P. Robinson; Enrique Mallada (CDC, 2018)

A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. - Chong You; Chi Li; Daniel P. Robinson; René Vidal (ECCV (9), 2018)

ADMM and Accelerated ADMM as Continuous Dynamical Systems. - Guilherme França; Daniel P. Robinson; René Vidal (ICML, 2018)

Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms. - Zhihui Zhu; Yifan Wang; Daniel P. Robinson; Daniel Q. Naiman; René Vidal; Manolis C. Tsakiris (NeurIPS, 2018)

A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis. - Hao Jiang; Daniel P. Robinson; René Vidal; Chong You (Comput. Optim. Appl., 2018)

Sparse Recovery over Graph Incidence Matrices: Polynomial Time Guarantees and Location Dependent Performance. - Mengnan Zhao; M. Devrim Kaba; René Vidal; Daniel P. Robinson; Enrique Mallada (CoRR, 2018)

Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms. - Zhihui Zhu; Yifan Wang; Daniel P. Robinson; Daniel Q. Naiman; René Vidal; Manolis C. Tsakiris (CoRR, 2018)

Concise complexity analyses for trust region methods. - Frank E. Curtis; Zachary Lubberts; Daniel P. Robinson (Optim. Lett., 2018)

FaRSA for ℓ1-regularized convex optimization: local convergence and numerical experience. - Tianyi Chen; Frank E. Curtis; Daniel P. Robinson (Optim. Methods Softw., 2018)

Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization. - Frank E. Curtis; Daniel P. Robinson; Mohammadreza Samadi (SIAM J. Optim., 2018)

Is an Affine Constraint Needed for Affine Subspace Clustering? - Chong You; Chun-Guang Li; Daniel P. Robinson; René Vidal (ICCV, 2019)

Noisy Dual Principal Component Pursuit. - Tianyu Ding; Zhihui Zhu; Tianjiao Ding; Yunchen Yang; Daniel P. Robinson; Manolis C. Tsakiris; René Vidal (ICML, 2019)

A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning. - Zhihui Zhu; Tianyu Ding; Daniel P. Robinson; Manolis C. Tsakiris; René Vidal (NeurIPS, 2019)

Gradient Flows and Accelerated Proximal Splitting Methods. - Guilherme França; Daniel P. Robinson; René Vidal (CoRR, 2019)

Generalized Nullspace Property for Structurally Sparse Signals. - Mustafa Devrim Kaba; Mengnan Zhao; René Vidal; Daniel P. Robinson; Enrique Mallada (CoRR, 2019)

Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. - Daniel P. Robinson; René Vidal; Chong You (CoRR, 2019)

Exploiting negative curvature in deterministic and stochastic optimization. - Frank E. Curtis; Daniel P. Robinson (Math. Program., 2019)

Robust Homography Estimation via Dual Principal Component Pursuit. - Tianjiao Ding; Yunchen Yang; Zhihui Zhu; Daniel P. Robinson; René Vidal; Laurent Kneip; Manolis C. Tsakiris (CVPR, 2020)

Conformal Symplectic and Relativistic Optimization. - Guilherme França; Jeremias Sulam; Daniel P. Robinson; René Vidal (NeurIPS, 2020)

A Shifted Primal-Dual Penalty-Barrier Method for Nonlinear Optimization. - Philip E. Gill; Vyacheslav Kungurtsev; Daniel P. Robinson (SIAM J. Optim., 2020)

Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms. - Tianyu Ding; Zhihui Zhu; Manolis C. Tsakiris; René Vidal; Daniel P. Robinson (AISTATS, 2021)

Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach. - Tianyu Ding; Zhihui Zhu; René Vidal; Daniel P. Robinson (ICML, 2021)

A Nullspace Property for Subspace-Preserving Recovery. - Mustafa Devrim Kaba; Chong You; Daniel P. Robinson; Enrique Mallada; René Vidal (ICML, 2021)

Boosting RANSAC via Dual Principal Component Pursuit. - Yunchen Yang; Xinyue Zhang; Tianjiao Ding; Daniel P. Robinson; René Vidal; Manolis C. Tsakiris (CoRR, 2021)

Regional complexity analysis of algorithms for nonconvex smooth optimization. - Frank E. Curtis; Daniel P. Robinson (Math. Program., 2021)

Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. - Albert S. Berahas; Frank E. Curtis; Daniel P. Robinson; Baoyu Zhou (SIAM J. Optim., 2021)

Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization. - Frank E. Curtis; Daniel P. Robinson; Clément W. Royer; Stephen J. Wright 001 (SIAM J. Optim., 2021)

What is the Largest Sparsity Pattern That Can Be Recovered by 1-Norm Minimization? - Mustafa Devrim Kaba; Mengnan Zhao; René Vidal; Daniel P. Robinson; Enrique Mallada (IEEE Trans. Inf. Theory, 2021)

Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. - Chong You; Chi Li; Daniel P. Robinson; René Vidal (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer. - Frank E. Curtis; Yutong Dai 002; Daniel P. Robinson (SIAM J. Optim., 2022)

A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization. - Yutong Dai 002; Guanyi Wang; Frank E. Curtis; Daniel P. Robinson (AISTATS, 2023)

An Adaptive Half-Space Projection Method for Stochastic Optimization Problems with Group Sparse Regularization. - Yutong Dai 002; Tianyi Chen; Guanyi Wang; Daniel P. Robinson (Trans. Mach. Learn. Res., 2023)

A Nonsmooth Dynamical Systems Perspective on Accelerated Extensions of ADMM. - Guilherme França; Daniel P. Robinson; René Vidal (IEEE Trans. Autom. Control., 2023)

Geometric Analysis of Nonlinear Manifold Clustering. - Nimita Shinde; Tianjiao Ding; Daniel P. Robinson; René Vidal (NeurIPS, 2024)

Using Synthetic Data to Mitigate Unfairness and Preserve Privacy through Single-Shot Federated Learning. - Chia-Yuan Wu; Frank E. Curtis; Daniel P. Robinson (CoRR, 2024)

A Stochastic Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Equality-Constrained Optimization. - Frank E. Curtis; Daniel P. Robinson; Baoyu Zhou (INFORMS J. Optim., 2024)

A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear-Equality-Constrained Optimization with Rank-Deficient Jacobians. - Albert S. Berahas; Frank E. Curtis; Michael O'Neill 002; Daniel P. Robinson (Math. Oper. Res., 2024)

A proximal-gradient method for problems with overlapping group-sparse regularization: support identification complexity. - Yutong Dai 002; Daniel P. Robinson (Optim. Methods Softw., 2024)

Sequential Quadratic Optimization for Stochastic Optimization with Deterministic Nonlinear Inequality and Equality Constraints. - Frank E. Curtis; Daniel P. Robinson; Baoyu Zhou (SIAM J. Optim., 2024)

Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization. - Frank E. Curtis; Michael J. O'Neill 002; Daniel P. Robinson (Math. Program., 2024)

Fair machine learning through constrained stochastic optimization and an ε-constraint method. - Frank E. Curtis; Suyun Liu; Daniel P. Robinson (Optim. Lett., 2024)

Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression. - Xiaoyi Qu; David Aponte; Colby R. Banbury; Daniel P. Robinson; Tianyu Ding; Kazuhito Koishida; Ilya Zharkov; Tianyi Chen (CVPR, 2025)

A Stochastic-Gradient-Based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems. - Frank E. Curtis; Vyacheslav Kungurtsev; Daniel P. Robinson; Qi Wang (SIAM J. Optim., 2025)

Fair Supervised Learning Through Constraints on Smooth Nonconvex Unfairness-Measure Surrogates. - Zahra Khatti; Daniel P. Robinson; Frank E. Curtis (CoRR, 2025)