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ORCIDStephen J. Wright 0001
Person information
- affiliation: University of Wisconsin-Madison, Deartment of Computer Sciences, WI, USA
- affiliation (former): Argonne National Laboratory, Mathematics and Computer Science Division, IL, USA
- affiliation (former): North Carolina State University, Mathematics Department, Raleigh, NC, USA
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2020 – today
- 2024
[j101]Yue Xie
, Stephen J. Wright:
Complexity of a projected Newton-CG method for optimization with bounds. Math. Program. 207(1): 107-144 (2024)- [c57]Ahmet Alacaoglu, Stephen J. Wright:
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. AISTATS 2024: 4627-4635 - [c56]Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright:
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity. ICML 2024 - [c55]Charles Andrew Dickens, Changyu Gao, Connor Pryor, Stephen J. Wright, Lise Getoor:
Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning. ICML 2024 - [c54]Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright:
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses. ICML 2024 - [c53]Andrew Lowy, Jonathan R. Ullman, Stephen J. Wright:
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization. ICML 2024 - [i54]Ruhui Jin, Martin Guerra, Qin Li, Stephen J. Wright:
Optimal experimental design via gradient flow. CoRR abs/2401.07806 (2024) - [i53]Charles Dickens, Changyu Gao, Connor Pryor, Stephen J. Wright, Lise Getoor:
Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning. CoRR abs/2401.09651 (2024) - [i52]Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright:
Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity. CoRR abs/2402.05071 (2024) - [i51]Andrew Lowy, Jonathan R. Ullman, Stephen J. Wright:
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization. CoRR abs/2402.11173 (2024) - [i50]Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright:
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. CoRR abs/2403.10547 (2024) - [i49]Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright:
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses. CoRR abs/2407.09690 (2024) - [i48]Charles Dickens, Connor Pryor, Changyu Gao, Alon Albalak, Eriq Augustine, William Yang Wang, Stephen J. Wright, Lise Getoor:
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic Systems. CoRR abs/2407.09693 (2024) - [i47]Ruhui Jin, Qin Li, Stephen O. Mussmann, Stephen J. Wright:
Continuous nonlinear adaptive experimental design with gradient flow. CoRR abs/2411.14332 (2024) - [i46]Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright:
Optimal Rates for Robust Stochastic Convex Optimization. CoRR abs/2412.11003 (2024) - 2023
- [j100]Michael O'Neill, Stephen J. Wright:
A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees. J. Mach. Learn. Res. 24: 10:1-10:34 (2023) - [j99]Kristin P. Bennett, Michael C. Ferris, Jong-Shi Pang, Mikhail V. Solodov, Stephen J. Wright:
Special Issue: Hierarchical Optimization. Math. Program. 198(2): 1121-1123 (2023) - [j98]Nam Ho-Nguyen, Stephen J. Wright:
Adversarial classification via distributional robustness with Wasserstein ambiguity. Math. Program. 198(2): 1411-1447 (2023) - [c52]Xufeng Cai, Chaobing Song, Stephen J. Wright, Jelena Diakonikolas:
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization. ICML 2023: 3469-3494 - [c51]Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright:
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. NeurIPS 2023 - [i45]Matteo Croci, Karen E. Willcox, Stephen J. Wright:
Multi-output multilevel best linear unbiased estimators via semidefinite programming. CoRR abs/2301.07831 (2023) - [i44]Changyu Gao, Stephen J. Wright:
Differentially Private Optimization for Smooth Nonconvex ERM. CoRR abs/2302.04972 (2023) - [i43]Shi Chen, Zhiyan Ding, Qin Li, Stephen J. Wright:
On optimal bases for multiscale PDEs and Bayesian homogenization. CoRR abs/2305.12303 (2023) - [i42]Yewei Xu, Shi Chen, Qin Li, Stephen J. Wright:
Correcting auto-differentiation in neural-ODE training. CoRR abs/2306.02192 (2023) - [i41]Shi Chen, Qin Li, Oliver Tse, Stephen J. Wright:
Accelerating optimization over the space of probability measures. CoRR abs/2310.04006 (2023) - [i40]Shuyao Li, Stephen J. Wright:
A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees. CoRR abs/2310.18841 (2023) - [i39]Ahmet Alacaoglu, Stephen J. Wright:
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. CoRR abs/2311.00678 (2023) - 2022
- [j97]Zhiyan Ding, Shi Chen, Qin Li, Stephen J. Wright:
Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis. J. Mach. Learn. Res. 23: 48:1-48:65 (2022) - [j96]Shi Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
Manifold Learning and Nonlinear Homogenization. Multiscale Model. Simul. 20(3): 1093-1126 (2022) - [c50]Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas:
Coordinate Linear Variance Reduction for Generalized Linear Programming. NeurIPS 2022 - [i38]Ahmet Alacaoglu, Volkan Cevher, Stephen J. Wright:
On the Complexity of a Practical Primal-Dual Coordinate Method. CoRR abs/2201.07684 (2022) - [i37]Xufeng Cai, Chaobing Song, Stephen J. Wright, Jelena Diakonikolas:
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization. CoRR abs/2212.05088 (2022) - 2021
- [j95]Pratyush Kumar, James B. Rawlings, Stephen J. Wright:
Industrial, large-scale model predictive control with structured neural networks. Comput. Chem. Eng. 150: 107291 (2021) - [j94]Cong Han Lim, Jeffrey T. Linderoth, James R. Luedtke, Stephen J. Wright:
Parallelizing Subgradient Methods for the Lagrangian Dual in Stochastic Mixed-Integer Programming. INFORMS J. Optim. 3(1): 1-22 (2021) - [j93]Axel Böhm, Stephen J. Wright:
Variable Smoothing for Weakly Convex Composite Functions. J. Optim. Theory Appl. 188(3): 628-649 (2021) - [j92]Yue Xie, Stephen J. Wright:
Complexity of Proximal Augmented Lagrangian for Nonconvex Optimization with Nonlinear Equality Constraints. J. Sci. Comput. 86(3): 38 (2021) - [j91]Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
A Low-Rank Schwarz Method for Radiative Transfer Equation With Heterogeneous Scattering Coefficient. Multiscale Model. Simul. 19(2): 775-801 (2021) - [j90]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): 518-544 (2021) - [c49]Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright:
Random Coordinate Underdamped Langevin Monte Carlo. AISTATS 2021: 2701-2709 - [c48]Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright:
Random Coordinate Langevin Monte Carlo. COLT 2021: 1683-1710 - [c47]Chaobing Song, Stephen J. Wright, Jelena Diakonikolas:
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums. ICML 2021: 9824-9834 - [i36]Chaobing Song, Stephen J. Wright, Jelena Diakonikolas:
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums. CoRR abs/2102.13643 (2021) - [i35]Aydin Buluç, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony M. DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary L. Myers, Jelani Nelson, Juan M. Restrepo, C. Seshadhri, Draguna L. Vrabie, Brendt Wohlberg, Stephen J. Wright, Chao Yang, Peter Zwart:
Randomized Algorithms for Scientific Computing (RASC). CoRR abs/2104.11079 (2021) - [i34]Zhiyan Ding, Shi Chen, Qin Li, Stephen J. Wright:
Overparameterization of deep ResNet: zero loss and mean-field analysis. CoRR abs/2105.14417 (2021) - [i33]Zhiyan Ding, Shi Chen, Qin Li, Stephen J. Wright:
On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime. CoRR abs/2110.02926 (2021) - [i32]Chaobing Song, Cheuk Yin Lin, Stephen J. Wright, Jelena Diakonikolas:
Coordinate Linear Variance Reduction for Generalized Linear Programming. CoRR abs/2111.01842 (2021) - [i31]Shi Chen, Zhiyan Ding, Qin Li, Stephen J. Wright:
A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks. CoRR abs/2111.02280 (2021) - [i30]Ke Chen, Shi Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
Low-rank approximation for multiscale PDEs. CoRR abs/2111.12904 (2021) - 2020
- [j89]Ching-pei Lee, Stephen J. Wright:
Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization. J. Optim. Theory Appl. 185(1): 151-187 (2020) - [j88]Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
Randomized Sampling for Basis Function Construction in Generalized Finite Element Methods. Multiscale Model. Simul. 18(2): 1153-1177 (2020) - [j87]Stephen J. Wright, Ching-pei Lee:
Analyzing random permutations for cyclic coordinate descent. Math. Comput. 89(325): 2217-2248 (2020) - [j86]Clément W. Royer, Michael O'Neill, Stephen J. Wright:
A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization. Math. Program. 180(1): 451-488 (2020) - [j85]Mert Gürbüzbalaban, Asuman E. Ozdaglar, Nuri Denizcan Vanli, Stephen J. Wright:
Randomness and permutations in coordinate descent methods. Math. Program. 181(2): 349-376 (2020) - [j84]Ke Chen, Qin Li, Kit Newton, Stephen J. Wright:
Structured Random Sketching for PDE Inverse Problems. SIAM J. Matrix Anal. Appl. 41(4): 1742-1770 (2020) - [j83]Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
Random Sampling and Efficient Algorithms for Multiscale PDEs. SIAM J. Sci. Comput. 42(5): A2974-A3005 (2020) - [i29]Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page:
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. CoRR abs/2005.06083 (2020) - [i28]Nam Ho-Nguyen, Stephen J. Wright:
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity. CoRR abs/2005.13815 (2020) - [i27]Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright:
Random Coordinate Langevin Monte Carlo. CoRR abs/2010.01405 (2020) - [i26]Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen J. Wright:
Random Coordinate Underdamped Langevin Monte Carlo. CoRR abs/2010.11366 (2020) - [i25]Shi Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
Manifold Learning and Nonlinear Homogenization. CoRR abs/2011.00568 (2020)
2010 – 2019
- 2019
- [j82]Ching-pei Lee, Stephen J. Wright:
Inexact Successive quadratic approximation for regularized optimization. Comput. Optim. Appl. 72(3): 641-674 (2019) - [j81]Eric D. Glendening, Stephen J. Wright, Frank Weinhold:
Efficient optimization of natural resonance theory weightings and bond orders by gram-based convex programming. J. Comput. Chem. 40(23): 2028-2035 (2019) - [j80]Fanhai Zeng, Ian W. Turner, Kevin Burrage, Stephen J. Wright:
A discrete least squares collocation method for two-dimensional nonlinear time-dependent partial differential equations. J. Comput. Phys. 394: 177-199 (2019) - [j79]Michael O'Neill, Stephen J. Wright:
Behavior of accelerated gradient methods near critical points of nonconvex functions. Math. Program. 176(1-2): 403-427 (2019) - [j78]Huikun Zhang, Spencer S. Ericksen, Ching-pei Lee, Gene E. Ananiev, Nathan Wlodarchak, Peng Yu, Julie C. Mitchell, Anthony Gitter, Stephen J. Wright, F. Michael Hoffmann, Scott A. Wildman, Michael A. Newton:
Predicting kinase inhibitors using bioactivity matrix derived informer sets. PLoS Comput. Biol. 15(8) (2019) - [c46]Gábor Braun, Sebastian Pokutta, Dan Tu, Stephen J. Wright:
Blended Conditonal Gradients. ICML 2019: 735-743 - [c45]Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak:
Bilinear Bandits with Low-rank Structure. ICML 2019: 3163-3172 - [c44]Ching-pei Lee, Stephen J. Wright:
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems. ICML 2019: 3754-3762 - [i24]Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak:
Bilinear Bandits with Low-rank Structure. CoRR abs/1901.02470 (2019) - [i23]Zachary Charles, Shashank Rajput, Stephen J. Wright, Dimitris S. Papailiopoulos:
Convergence and Margin of Adversarial Training on Separable Data. CoRR abs/1905.09209 (2019) - [i22]Ke Chen, Qin Li, Jianfeng Lu, Stephen J. Wright:
A low-rank Schwarz method for radiative transport equation with heterogeneous scattering coefficient. CoRR abs/1906.02176 (2019) - [i21]Ke Chen, Qin Li, Stephen J. Wright:
Schwarz iteration method for elliptic equation with rough media based on random sampling. CoRR abs/1910.02022 (2019) - [i20]Ching-pei Lee, Cong Han Lim, Stephen J. Wright:
A Distributed Quasi-Newton Algorithm for Primal and Dual Regularized Empirical Risk Minimization. CoRR abs/1912.06508 (2019) - [i19]Soroosh Khoram, Stephen J. Wright, Jing Li:
Interleaved Composite Quantization for High-Dimensional Similarity Search. CoRR abs/1912.08756 (2019) - 2018
- [j77]Clément W. Royer, Stephen J. Wright:
Complexity Analysis of Second-Order Line-Search Algorithms for Smooth Nonconvex Optimization. SIAM J. Optim. 28(2): 1448-1477 (2018) - [j76]Taedong Kim, Stephen J. Wright:
PMU Placement for Line Outage Identification via Multinomial Logistic Regression. IEEE Trans. Smart Grid 9(1): 122-131 (2018) - [c43]Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright:
Training Set Debugging Using Trusted Items. AAAI 2018: 4482-4489 - [c42]Bin Hu, Stephen J. Wright, Laurent Lessard:
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs. ICML 2018: 2043-2052 - [c41]Ching-pei Lee, Cong Han Lim, Stephen J. Wright:
A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization. KDD 2018: 1646-1655 - [c40]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. NeurIPS 2018: 9872-9883 - [c39]Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page:
Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. UAI 2018: 156-166 - [i18]Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright:
Training Set Debugging Using Trusted Items. CoRR abs/1801.08019 (2018) - [i17]Ching-pei Lee, Cong Han Lim, Stephen J. Wright:
A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization. CoRR abs/1803.01370 (2018) - [i16]Gábor Braun, Sebastian Pokutta, Dan Tu, Stephen J. Wright:
Blended Conditional Gradients: the unconditioning of conditional gradients. CoRR abs/1805.07311 (2018) - [i15]Bin Hu, Stephen J. Wright, Laurent Lessard:
Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs. CoRR abs/1806.03677 (2018) - [i14]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. CoRR abs/1806.04090 (2018) - 2017
- [c38]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Improved Strongly Adaptive Online Learning using Coin Betting. AISTATS 2017: 943-951 - [c37]Cong Han Lim, Stephen J. Wright:
k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms. NIPS 2017: 284-292 - [i13]Ching-pei Lee, Stephen J. Wright:
Using Neural Networks to Detect Line Outages from PMU Data. CoRR abs/1710.05916 (2017) - [i12]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Online Learning for Changing Environments using Coin Betting. CoRR abs/1711.02545 (2017) - 2016
- [j75]Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor:
Online algorithms for factorization-based structure from motion. Comput. Vis. Image Underst. 150: 139-152 (2016) - [j74]Ji Liu, Stephen J. Wright:
An accelerated randomized Kaczmarz algorithm. Math. Comput. 85(297): 153-178 (2016) - [j73]Adrian S. Lewis, Stephen J. Wright:
A proximal method for composite minimization. Math. Program. 158(1-2): 501-546 (2016) - [j72]Simon Haykin, Stephen J. Wright, Yoshua Bengio:
Big Data: Theoretical Aspects [Scanning the Issue]. Proc. IEEE 104(1): 8-10 (2016) - [j71]Taedong Kim, Stephen J. Wright, Daniel Bienstock, Sean Harnett:
Analyzing Vulnerability of Power Systems with Continuous Optimization Formulations. IEEE Trans. Netw. Sci. Eng. 3(3): 132-146 (2016) - [c36]Cong Han Lim, Stephen J. Wright:
Efficient Bregman Projections onto the Permutahedron and Related Polytopes. AISTATS 2016: 1205-1213 - [c35]Yasin Abbasi-Yadkori, Peter L. Bartlett, Stephen J. Wright:
A Fast and Reliable Policy Improvement Algorithm. AISTATS 2016: 1338-1346 - [i11]Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, Stephen J. Wright:
Improved Strongly Adaptive Online Learning using Coin Betting. CoRR abs/1610.04578 (2016) - 2015
- [j70]Laura Balzano, Stephen J. Wright:
Local Convergence of an Algorithm for Subspace Identification from Partial Data. Found. Comput. Math. 15(5): 1279-1314 (2015) - [j69]Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar:
An asynchronous parallel stochastic coordinate descent algorithm. J. Mach. Learn. Res. 16: 285-322 (2015) - [j68]Stephen J. Wright:
Coordinate descent algorithms. Math. Program. 151(1): 3-34 (2015) - [j67]Ji Liu, Stephen J. Wright:
Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties. SIAM J. Optim. 25(1): 351-376 (2015) - [j66]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward-Backward Greedy Algorithms for Atomic Norm Regularization. IEEE Trans. Signal Process. 63(21): 5798-5811 (2015) - 2014
- [j65]Stephen J. Wright:
Research Spotlights. SIAM Rev. 56(2): 259 (2014) - [j64]Stephen J. Wright:
Research Spotlights. SIAM Rev. 56(3): 459 (2014) - [c34]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward - Backward greedy algorithms for signal demixing. ACSSC 2014: 437-441 - [c33]Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar:
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm. ICML 2014: 469-477 - [c32]Cong Han Lim, Stephen J. Wright:
Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems. NIPS 2014: 2168-2176 - [c31]Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor:
Online algorithms for factorization-based structure from motion. WACV 2014: 37-44 - [i10]Ji Liu, Stephen J. Wright, Srikrishna Sridhar:
An Asynchronous Parallel Randomized Kaczmarz Algorithm. CoRR abs/1401.4780 (2014) - [i9]Nikhil Rao, Parikshit Shah, Stephen J. Wright:
Forward - Backward Greedy Algorithms for Atomic Norm Regularization. CoRR abs/1404.5692 (2014) - 2013
- [j63]Caroline Uhler, Stephen J. Wright:
Packing Ellipsoids with Overlap. SIAM Rev. 55(4): 671-706 (2013) - [j62]Stephen J. Wright, Dimitri Kanevsky, Li Deng, Xiaodong He, Georg Heigold, Haizhou Li:
Optimization Algorithms and Applications for Speech and Language Processing. IEEE Trans. Speech Audio Process. 21(11): 2231-2243 (2013) - [c30]Laura Balzano, Stephen J. Wright:
On GROUSE and incremental SVD. CAMSAP 2013: 1-4 - [c29]Nikhil Rao, Parikshit Shah, Stephen J. Wright, Robert D. Nowak:
A greedy forward-backward algorithm for atomic norm constrained minimization. ICASSP 2013: 5885-5889 - [c28]Stephen J. Wright:
Optimization in learning and data analysis. KDD 2013: 3 - [c27]Srikrishna Sridhar, Stephen J. Wright, Christopher Ré, Ji Liu, Victor Bittorf, Ce Zhang:
An Approximate, Efficient LP Solver for LP Rounding. NIPS 2013: 2895-2903 - [i8]