Daniel P. Robinson

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 54

Top Topics

Augmented Lagrangian

Orthogonal Matching Pursuit

Subspace Clustering

Top Venues

Publications

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)
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)
Guilherme França, Daniel P. Robinson, René Vidal
A Nonsmooth Dynamical Systems Perspective on Accelerated Extensions of ADMM. IEEE Trans. Autom. Control. 68 (5) (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)
Yutong Dai, Tianyi Chen, Guanyi Wang, Daniel P. Robinson
An Adaptive Half-Space Projection Method for Stochastic Optimization Problems with Group Sparse Regularization. Trans. Mach. Learn. Res. 2023 (2023)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 44 (5) (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)
Mustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal
A Nullspace Property for Subspace-Preserving Recovery. ICML (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)
Tianyu Ding, Zhihui Zhu, Manolis C. Tsakiris, René Vidal, Daniel P. Robinson
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms. AISTATS (2021)
Tianyu Ding, Zhihui Zhu, René Vidal, Daniel P. Robinson
Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach. ICML (2021)
Yunchen Yang, Xinyue Zhang, Tianjiao Ding, Daniel P. Robinson, René Vidal, Manolis C. Tsakiris
Boosting RANSAC via Dual Principal Component Pursuit. CoRR (2021)
Mustafa Devrim Kaba, Mengnan Zhao, René Vidal, Daniel P. Robinson, Enrique Mallada
What is the Largest Sparsity Pattern That Can Be Recovered by 1-Norm Minimization? IEEE Trans. Inf. Theory 67 (5) (2021)
Tianjiao Ding, Yunchen Yang, Zhihui Zhu, Daniel P. Robinson, René Vidal, Laurent Kneip, Manolis C. Tsakiris
Robust Homography Estimation via Dual Principal Component Pursuit. CVPR (2020)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces. CoRR (2020)
Albert S. Berahas, Frank E. Curtis, Daniel P. Robinson, Baoyu Zhou
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization. CoRR (2020)
Philip E. Gill, Vyacheslav Kungurtsev, Daniel P. Robinson
A Shifted Primal-Dual Penalty-Barrier Method for Nonlinear Optimization. SIAM J. Optim. 30 (2) (2020)
Guilherme França, Jeremias Sulam, Daniel P. Robinson, René Vidal
Conformal Symplectic and Relativistic Optimization. NeurIPS (2020)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Is an Affine Constraint Needed for Affine Subspace Clustering? CoRR (2020)
Mustafa Devrim Kaba, Mengnan Zhao, René Vidal, Daniel P. Robinson, Enrique Mallada
Generalized Nullspace Property for Structurally Sparse Signals. CoRR (2019)
Frank E. Curtis, Daniel P. Robinson
Exploiting negative curvature in deterministic and stochastic optimization. Math. Program. 176 (1-2) (2019)
Daniel P. Robinson, René Vidal, Chong You
Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis. CoRR (2019)
Tianyu Ding, Zhihui Zhu, Tianjiao Ding, Yunchen Yang, Daniel P. Robinson, Manolis C. Tsakiris, René Vidal
Noisy Dual Principal Component Pursuit. ICML (2019)
Zhihui Zhu, Tianyu Ding, Daniel P. Robinson, Manolis C. Tsakiris, René Vidal
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning. NeurIPS (2019)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Is an Affine Constraint Needed for Affine Subspace Clustering? ICCV (2019)
Guilherme França, Daniel P. Robinson, René Vidal
Gradient Flows and Accelerated Proximal Splitting Methods. CoRR (2019)
Zhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, René Vidal, Manolis C. Tsakiris
Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms. CoRR (2018)
Hao Jiang, Daniel P. Robinson, René Vidal, Chong You
A nonconvex formulation for low rank subspace clustering: algorithms and convergence analysis. Comput. Optim. Appl. 70 (2) (2018)
Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, Enrique Mallada
Sparse Recovery over Graph Incidence Matrices. CDC (2018)
Guilherme França, Daniel P. Robinson, René Vidal
ADMM and Accelerated ADMM as Continuous Dynamical Systems. ICML (2018)
Chong You, Chi Li, Daniel P. Robinson, René Vidal
A Scalable Exemplar-Based Subspace Clustering Algorithm for Class-Imbalanced Data. ECCV (9) (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)
Mengnan Zhao, M. Devrim Kaba, René Vidal, Daniel P. Robinson, Enrique Mallada
Sparse Recovery over Graph Incidence Matrices: Polynomial Time Guarantees and Location Dependent Performance. CoRR (2018)
Zhihui Zhu, Yifan Wang, Daniel P. Robinson, Daniel Q. Naiman, René Vidal, Manolis C. Tsakiris
Dual Principal Component Pursuit: Improved Analysis and Efficient Algorithms. NeurIPS (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)
Nicholas I. M. Gould, Daniel P. Robinson
A dual gradient-projection method for large-scale strictly convex quadratic problems. Comput. Optim. Appl. 67 (1) (2017)
Daniel P. Robinson, Rachael Tappenden
A Flexible ADMM Algorithm for Big Data Applications. J. Sci. Comput. 71 (1) (2017)
Chong You, Daniel P. Robinson, René Vidal
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CoRR (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)
Philip E. Gill, Vyacheslav Kungurtsev, Daniel P. Robinson
A stabilized SQP method: superlinear convergence. Math. Program. 163 (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)
Chong You, Daniel P. Robinson, René Vidal
Provable Self-Representation Based Outlier Detection in a Union of Subspaces. CVPR (2017)
Daniel P. Robinson, Suchi Saria
Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. IJCAI (2016)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CVPR (2016)
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)
Chong You, Daniel P. Robinson, René Vidal
Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit. CVPR (2016)
Chong You, Claire Donnat, Daniel P. Robinson, René Vidal
A divide-and-conquer framework for large-scale subspace clustering. ACSSC (2016)
Daniel P. Robinson, Suchi Saria
Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models. CoRR (2016)
Chong You, Chun-Guang Li, Daniel P. Robinson, René Vidal
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering. CoRR (2016)
Nicholas I. M. Gould, Yueling Loh, Daniel P. Robinson
A Nonmonotone Filter SQP Method: Local Convergence and Numerical Results. SIAM J. Optim. 25 (3) (2015)
Hassan Mohy-ud-Din, Daniel P. Robinson
A Solver for Nonconvex Bound-Constrained Quadratic Optimization. SIAM J. Optim. 25 (4) (2015)
Congyuan Yang, Daniel P. Robinson, René Vidal
Sparse Subspace Clustering with Missing Entries. ICML (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)
Daniel P. Robinson
Primal-Dual Active-Set Methods for Large-Scale Optimization. J. Optim. Theory Appl. 166 (1) (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)
Nicholas I. M. Gould, Yueling Loh, Daniel P. Robinson
A Filter Method with Unified Step Computation for Nonlinear Optimization. SIAM J. Optim. 24 (1) (2014)
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)
Daniel P. Robinson, Liming Feng, Jorge Nocedal, Jong-Shi Pang
Subspace Accelerated Matrix Splitting Algorithms for Asymmetric and Symmetric Linear Complementarity Problems. SIAM J. Optim. 23 (3) (2013)
Philip E. Gill, Daniel P. Robinson
A Globally Convergent Stabilized SQP Method. SIAM J. Optim. 23 (4) (2013)
Nicholas I. M. Gould, Dominique Orban, Daniel P. Robinson
Trajectory-following methods for large-scale degenerate convex quadratic programming. Math. Program. Comput. 5 (2) (2013)
Philip E. Gill, Daniel P. Robinson
A primal-dual augmented Lagrangian. Comput. Optim. Appl. 51 (1) (2012)
Nicholas I. M. Gould, Daniel P. Robinson
A Second Derivative SQP Method: Global Convergence. SIAM J. Optim. 20 (4) (2010)
Nicholas I. M. Gould, Daniel P. Robinson, H. Sue Thorne
On solving trust-region and other regularised subproblems in optimization. Math. Program. Comput. 2 (1) (2010)
Nicholas I. M. Gould, Daniel P. Robinson
A Second Derivative SQP Method: Local Convergence and Practical Issues. SIAM J. Optim. 20 (4) (2010)