Stephen J. Wright

Orcid: 0000-0001-6815-7379

Affiliations:
  • University of Wisconsin-Madison, Deartment of Computer Sciences, WI, USA
  • Argonne National Laboratory, Mathematics and Computer Science Division, IL, USA (former)
  • North Carolina State University, Mathematics Department, Raleigh, NC, USA (former)


According to our database1, Stephen J. Wright authored at least 185 papers between 1987 and 2024.

Collaborative distances:
  • Dijkstra number2 of two.
  • Erdős number3 of three.

Timeline

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Bibliography

2024
Complexity of a projected Newton-CG method for optimization with bounds.
Math. Program., September, 2024

A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic Systems.
CoRR, 2024

Extending the Reach of First-Order Algorithms for Nonconvex Min-Max Problems with Cohypomonotonicity.
CoRR, 2024

Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning.
CoRR, 2024

Optimal experimental design via gradient flow.
CoRR, 2024

How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Adversarial classification via distributional robustness with Wasserstein ambiguity.
Math. Program., April, 2023

Special Issue: Hierarchical Optimization.
Math. Program., April, 2023

A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees.
J. Mach. Learn. Res., 2023

A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees.
CoRR, 2023

Accelerating optimization over the space of probability measures.
CoRR, 2023

Correcting auto-differentiation in neural-ODE training.
CoRR, 2023

On optimal bases for multiscale PDEs and Bayesian homogenization.
CoRR, 2023

Differentially Private Optimization for Smooth Nonconvex ERM.
CoRR, 2023

Multi-output multilevel best linear unbiased estimators via semidefinite programming.
CoRR, 2023

Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization.
Proceedings of the International Conference on Machine Learning, 2023

2022
Manifold Learning and Nonlinear Homogenization.
Multiscale Model. Simul., September, 2022

Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis.
J. Mach. Learn. Res., 2022

On the Complexity of a Practical Primal-Dual Coordinate Method.
CoRR, 2022

Coordinate Linear Variance Reduction for Generalized Linear Programming.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Parallelizing Subgradient Methods for the Lagrangian Dual in Stochastic Mixed-Integer Programming.
INFORMS J. Optim., January, 2021

Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization.
SIAM J. Optim., 2021

A Low-Rank Schwarz Method for Radiative Transfer Equation With Heterogeneous Scattering Coefficient.
Multiscale Model. Simul., 2021

Complexity of Proximal Augmented Lagrangian for Nonconvex Optimization with Nonlinear Equality Constraints.
J. Sci. Comput., 2021

Variable Smoothing for Weakly Convex Composite Functions.
J. Optim. Theory Appl., 2021

Low-rank approximation for multiscale PDEs.
CoRR, 2021

A reduced order Schwarz method for nonlinear multiscale elliptic equations based on two-layer neural networks.
CoRR, 2021

On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime.
CoRR, 2021

Randomized Algorithms for Scientific Computing (RASC).
CoRR, 2021

Industrial, large-scale model predictive control with structured neural networks.
Comput. Chem. Eng., 2021

Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums.
Proceedings of the 38th International Conference on Machine Learning, 2021

Random Coordinate Langevin Monte Carlo.
Proceedings of the Conference on Learning Theory, 2021

Random Coordinate Underdamped Langevin Monte Carlo.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Random Sampling and Efficient Algorithms for Multiscale PDEs.
SIAM J. Sci. Comput., 2020

Structured Random Sketching for PDE Inverse Problems.
SIAM J. Matrix Anal. Appl., 2020

A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization.
Math. Program., 2020

Randomness and permutations in coordinate descent methods.
Math. Program., 2020

Analyzing random permutations for cyclic coordinate descent.
Math. Comput., 2020

Randomized Sampling for Basis Function Construction in Generalized Finite Element Methods.
Multiscale Model. Simul., 2020

Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization.
J. Optim. Theory Appl., 2020

2019
Predicting kinase inhibitors using bioactivity matrix derived informer sets.
PLoS Comput. Biol., 2019

Behavior of accelerated gradient methods near critical points of nonconvex functions.
Math. Program., 2019

A discrete least squares collocation method for two-dimensional nonlinear time-dependent partial differential equations.
J. Comput. Phys., 2019

Efficient optimization of natural resonance theory weightings and bond orders by gram-based convex programming.
J. Comput. Chem., 2019

Interleaved Composite Quantization for High-Dimensional Similarity Search.
CoRR, 2019

A Distributed Quasi-Newton Algorithm for Primal and Dual Regularized Empirical Risk Minimization.
CoRR, 2019

Schwarz iteration method for elliptic equation with rough media based on random sampling.
CoRR, 2019

A low-rank Schwarz method for radiative transport equation with heterogeneous scattering coefficient.
CoRR, 2019

Convergence and Margin of Adversarial Training on Separable Data.
CoRR, 2019

Inexact Successive quadratic approximation for regularized optimization.
Comput. Optim. Appl., 2019

First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bilinear Bandits with Low-rank Structure.
Proceedings of the 36th International Conference on Machine Learning, 2019

Blended Conditonal Gradients.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
PMU Placement for Line Outage Identification via Multinomial Logistic Regression.
IEEE Trans. Smart Grid, 2018

Complexity Analysis of Second-Order Line-Search Algorithms for Smooth Nonconvex Optimization.
SIAM J. Optim., 2018

Blended Conditional Gradients: the unconditioning of conditional gradients.
CoRR, 2018

Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

ATOMO: Communication-efficient Learning via Atomic Sparsification.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs.
Proceedings of the 35th International Conference on Machine Learning, 2018

Training Set Debugging Using Trusted Items.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Online Learning for Changing Environments using Coin Betting.
CoRR, 2017

Using Neural Networks to Detect Line Outages from PMU Data.
CoRR, 2017

k-Support and Ordered Weighted Sparsity for Overlapping Groups: Hardness and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Improved Strongly Adaptive Online Learning using Coin Betting.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Analyzing Vulnerability of Power Systems with Continuous Optimization Formulations.
IEEE Trans. Netw. Sci. Eng., 2016

Big Data: Theoretical Aspects [Scanning the Issue].
Proc. IEEE, 2016

A proximal method for composite minimization.
Math. Program., 2016

An accelerated randomized Kaczmarz algorithm.
Math. Comput., 2016

Online algorithms for factorization-based structure from motion.
Comput. Vis. Image Underst., 2016

Efficient Bregman Projections onto the Permutahedron and Related Polytopes.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

A Fast and Reliable Policy Improvement Algorithm.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Forward-Backward Greedy Algorithms for Atomic Norm Regularization.
IEEE Trans. Signal Process., 2015

Asynchronous Stochastic Coordinate Descent: Parallelism and Convergence Properties.
SIAM J. Optim., 2015

Coordinate descent algorithms.
Math. Program., 2015

An asynchronous parallel stochastic coordinate descent algorithm.
J. Mach. Learn. Res., 2015

Local Convergence of an Algorithm for Subspace Identification from Partial Data.
Found. Comput. Math., 2015

2014
Research Spotlights.
SIAM Rev., 2014

An Asynchronous Parallel Randomized Kaczmarz Algorithm.
CoRR, 2014

Beyond the Birkhoff Polytope: Convex Relaxations for Vector Permutation Problems.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Forward - Backward greedy algorithms for signal demixing.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013
Optimization Algorithms and Applications for Speech and Language Processing.
IEEE Trans. Speech Audio Process., 2013

Packing Ellipsoids with Overlap.
SIAM Rev., 2013

An Approximate, Efficient Solver for LP Rounding.
CoRR, 2013

An Approximate, Efficient LP Solver for LP Rounding.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Optimization in learning and data analysis.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A greedy forward-backward algorithm for atomic norm constrained minimization.
Proceedings of the IEEE International Conference on Acoustics, 2013

On GROUSE and incremental SVD.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

2012
Accelerated Block-coordinate Relaxation for Regularized Optimization.
SIAM J. Optim., 2012

Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning.
J. Mach. Learn. Res., 2012

Optimizing financial effects of HIE: a multi-party linear programming approach.
J. Am. Medical Informatics Assoc., 2012

Robust Dequantized Compressive Sensing
CoRR, 2012

The partitioned LASSO-patternsearch algorithm with application to gene expression data.
BMC Bioinform., 2012

ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines.
Proceedings of the ICPRAM 2012, 2012

Overview of large scale optimization for discriminative training in speech recognition.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Identifying Activity.
SIAM J. Optim., 2011

Conditions under which suboptimal nonlinear MPC is inherently robust.
Syst. Control. Lett., 2011

Approximate Stochastic Subgradient Estimation Training for Support Vector Machines
CoRR, 2011

Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning.
Proceedings of the 28th International Conference on Machine Learning, 2011

Convex approaches to model wavelet sparsity patterns.
Proceedings of the 18th IEEE International Conference on Image Processing, 2011

Inherently robust suboptimal nonlinear MPC: Theory and application.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Cooperative distributed model predictive control.
Syst. Control. Lett., 2010

Computational Methods for Sparse Solution of Linear Inverse Problems.
Proc. IEEE, 2010

Duality-based algorithms for total-variation-regularized image restoration.
Comput. Optim. Appl., 2010

Optimization Methods for Selecting Founder Populations for Captive Breeding of Endangered Species.
Proceedings of the Biocomputing 2010: Proceedings of the Pacific Symposium, 2010

Hierarchical cooperative distributed model predictive control.
Proceedings of the American Control Conference, 2010

2009
Sparse reconstruction by separable approximation.
IEEE Trans. Signal Process., 2009

An accelerated Newton method for equations with semismooth Jacobians and nonlinear complementarity problems.
Math. Program., 2009

Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

2008
Distributed MPC Strategies With Application to Power System Automatic Generation Control.
IEEE Trans. Control. Syst. Technol., 2008

Optimal design of thermally stable proteins.
Bioinform., 2008

Power Awareness in Network Design and Routing.
Proceedings of the INFOCOM 2008. 27th IEEE International Conference on Computer Communications, 2008

2007
Global optimization in protein docking using clustering, underestimation and semidefinite programming.
Optim. Methods Softw., 2007

Elastic-mode algorithms for mathematical programs with equilibrium constraints: global convergence and stationarity properties.
Math. Program., 2007

Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems.
J. Sel. Topics Signal Processing, 2007

Dissimilarity in Graph-Based Semi-Supervised Classification.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

An Optimization Framework for Conformal Radiation Treatment Planning.
INFORMS J. Comput., 2007

Fast, large-scale model predictive control by partial enumeration.
Autom., 2007

Creating operations research models to guide RHIO decision making.
Proceedings of the AMIA 2007, 2007

Linear programming with MATLAB.
MPS-SIAM series on optimization 7, SIAM, ISBN: 978-0-89871-643-6, 2007

2006
Active Set Identification in Nonlinear Programming.
SIAM J. Optim., 2006

Linear programing formulations and algorithms for radiotherapy treatment planning.
Optim. Methods Softw., 2006

The empirical behavior of sampling methods for stochastic programming.
Ann. Oper. Res., 2006

Approximating StreamingWindow Joins Under CPU Limitations.
Proceedings of the 22nd International Conference on Data Engineering, 2006

Distributed Output Feedback MPC for Power System Control.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006

Implementable distributed model predictive control with guaranteed performance properties.
Proceedings of the American Control Conference, 2006

2005
Simultaneous Variable Selection.
Technometrics, 2005

An Algorithm for Degenerate Nonlinear Programming with Rapid Local Convergence.
SIAM J. Optim., 2005

Stability and optimality of distributed model predictive control.
Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

Modeling Participation in the NHII: Operations Research Approach.
Proceedings of the AMIA 2005, 2005

5. Computational Grids for Stochastic Programming.
Proceedings of the Applications of Stochastic Programming, 2005

2004
Minimizing delivery cost in scalable streaming content distribution systems.
IEEE Trans. Multim., 2004

A Feasible Trust-Region Sequential Quadratic Programming Algorithm.
SIAM J. Optim., 2004

Some properties of regularization and penalization schemes for MPECs.
Optim. Methods Softw., 2004

Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming.
Comput. Optim. Appl., 2004

Mass Spectrum Labeling: Theory and Practice.
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 2004

2003
Object-oriented software for quadratic programming.
ACM Trans. Math. Softw., 2003

Existence and computation of infinite horizon model predictive control with active steady-state input constraints.
IEEE Trans. Autom. Control., 2003

Constraint identification and algorithm stabilization for degenerate nonlinear programs.
Math. Program., 2003

Decomposition Algorithms for Stochastic Programming on a Computational Grid.
Comput. Optim. Appl., 2003

An Approach to Optimizing Adaptive Parabolic PDE Solvers for the Grid.
Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS 2003), 2003

2002
Warm-Start Strategies in Interior-Point Methods for Linear Programming.
SIAM J. Optim., 2002

Modifying SQP for Degenerate Problems.
SIAM J. Optim., 2002

Properties of the Log-Barrier Function on Degenerate Nonlinear Programs.
Math. Oper. Res., 2002

Local Convergence of a Primal-Dual Method for Degenerate Nonlinear Programming.
Comput. Optim. Appl., 2002

Model-Based Control of Adaptive Applications: An Overview.
Proceedings of the 16th International Parallel and Distributed Processing Symposium (IPDPS 2002), 2002

Near-optimal adaptive control of a large grid application.
Proceedings of the 16th international conference on Supercomputing, 2002

Numerical Behavior of a Stabilized SQP Method for Degenerate NLP Problems.
Proceedings of the Global Optimization and Constraint Satisfaction, 2002

2001
Effects of Finite-Precision Arithmetic on Interior-Point Methods for Nonlinear Programming.
SIAM J. Optim., 2001

On reduced convex QP formulations of monotone LCPs.
Math. Program., 2001

On the convergence of the Newton/log-barrier method.
Math. Program., 2001

2000
Superlinear Convergence of an Interior-Point Method Despite Dependent Constraints.
Math. Oper. Res., 2000

1999
Optimization Case Studies in the NEOS Guide.
SIAM Rev., 1999

Modified Cholesky Factorizations in Interior-Point Algorithms for Linear Programming.
SIAM J. Optim., 1999

The role of linear objective functions in barrier methods.
Math. Program., 1999

Recent Developments in Interior-Point Methods.
Proceedings of the System Modelling and Optimization: Methods, 1999

Numerical Optimization
Springer, ISBN: 978-0-387-22742-9, 1999

1998
Superlinear Convergence of a Stabilized SQP Method to a Degenerate Solution.
Comput. Optim. Appl., 1998

1997
pPCx: Parallel Software for Linear Programming.
Proceedings of the Eighth SIAM Conference on Parallel Processing for Scientific Computing, 1997

Primal-Dual Interior-Point Methods.
Other Titles in Applied Mathematics, SIAM, ISBN: 978-1-61197-145-3, 1997

1996
A Superlinear Infeasible-Interior-Point Affine Scaling Algorithm for LCP.
SIAM J. Optim., 1996

A superquadratic infeasible-interior-point method for linear complementarity problems.
Math. Program., 1996

A Superlinear Infeasible-Interior-Point Algorithm for Monotone Complementarity Problems.
Math. Oper. Res., 1996

A path-following interior-point algorithm for linear and quadratic problems.
Ann. Oper. Res., 1996

1995
Stability of Linear Equations Solvers in Interior-Point Methods.
SIAM J. Matrix Anal. Appl., 1995

Superlinear primal-dual affine scaling algorithms for LCP.
Math. Program., 1995

1994
An infeasible-interior-point algorithm for linear complementarity problems.
Math. Program., 1994

Local convergence of interior-point algorithms for degenerate monotone LCP.
Comput. Optim. Appl., 1994

1993
A Collection of Problems for Which Gaussian Elimination with Partial Pivoting is Unstable.
SIAM J. Sci. Comput., 1993

1992
Stable Parallel Algorithms for Two-Point Boundary Value Problems.
SIAM J. Sci. Comput., 1992

An Interior-Point Algorithm for Linearly Constrained Optimization.
SIAM J. Optim., 1992

1991
Parallel Algorithms for Banded Linear Systems.
SIAM J. Sci. Comput., 1991

Partitioned Dynamic Programming for Optimal Control.
SIAM J. Optim., 1991

Sequential quadratic programming for certain parameter identification problems.
Math. Program., 1991

1990
Adaptation of a Two-Point Boundary Value Problem Solver to a Vector-Multiprocessor Environment.
SIAM J. Sci. Comput., 1990

Solution of discrete-time optimal control problems on parallel computers.
Parallel Comput., 1990

1989
An inexact algorithm for composite nondifferentiable optimization.
Math. Program., 1989

1987
Local properties of inexact methods for minimizing nonsmooth composite functions.
Math. Program., 1987


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