Stephen P. Boyd

ORCID

Publication Activity (10 Years)

Years Active: 1986-2024
Publications (10 Years): 121

Top Venues

CoRR

CDC

J. Optim. Theory Appl.

ACC

Publications

Joshua Ott, Mykel J. Kochenderfer, Stephen P. Boyd
Approximate Sequential Optimization for Informative Path Planning. CoRR (2024)
Philipp Schiele, Eric Luxenberg, Stephen P. Boyd
Disciplined Saddle Programming. Trans. Mach. Learn. Res. 2024 (2024)
Eric Luxenberg, Philipp Schiele, Stephen P. Boyd
Robust Bond Portfolio Construction via Convex-Concave Saddle Point Optimization. J. Optim. Theory Appl. 201 (3) (2024)
Tobia Marcucci, Parth Nobel, Russ Tedrake, Stephen P. Boyd
Fast Path Planning Through Large Collections of Safe Boxes. IEEE Trans. Robotics 40 (2024)
Philipp Schiele, Eric Luxenberg, Stephen P. Boyd
Disciplined Saddle Programming. CoRR (2023)
Ziheng Cheng, Junzi Zhang, Akshay Agrawal, Stephen P. Boyd
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified Models. CoRR (2023)
Shane T. Barratt, Stephen P. Boyd
Fitting feature-dependent Markov chains. J. Glob. Optim. 87 (2) (2023)
Parth Nobel, Akshay Agrawal, Stephen P. Boyd
Computing tighter bounds on the n-queens constant via Newton's method. Optim. Lett. 17 (5) (2023)
Bennet E. Meyers, Stephen P. Boyd
Signal Decomposition Using Masked Proximal Operators. Found. Trends Signal Process. 17 (1) (2023)
Eric Luxenberg, Dhruv Malik, Yuanzhi Li, Aarti Singh, Stephen P. Boyd
Specifying and Solving Robust Empirical Risk Minimization Problems Using CVXPY. CoRR (2023)
Parth Nobel, Emmanuel J. Candès, Stephen P. Boyd
Tractable Evaluation of Stein's Unbiased Risk Estimate With Convex Regularizers. IEEE Trans. Signal Process. 71 (2023)
Tobia Marcucci, Parth Nobel, Russ Tedrake, Stephen P. Boyd
Fast Path Planning Through Large Collections of Safe Boxes. CoRR (2023)
Mehmet G. Ogut, Bennet E. Meyers, Stephen P. Boyd
PV Fleet Modeling via Smooth Periodic Gaussian Copula. CoRR (2023)
Maolin Wang, Ian McInerney, Bartolomeo Stellato, Stephen P. Boyd, Hayden Kwok-Hay So
RSQP: Problem-specific Architectural Customization for Accelerated Convex Quadratic Optimization. ISCA (2023)
Shane T. Barratt, Stephen P. Boyd
Stochastic Control With Affine Dynamics and Extended Quadratic Costs. IEEE Trans. Autom. Control. 67 (1) (2022)
Nir Shlezinger, Yonina C. Eldar, Stephen P. Boyd
Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization. CoRR (2022)
Maximilian Schaller, Goran Banjac, Steven Diamond, Akshay Agrawal, Bartolomeo Stellato, Stephen P. Boyd
Embedded Code Generation With CVXPY. IEEE Control. Syst. Lett. 6 (2022)
Anqi Fu, Lei Xing, Stephen P. Boyd
Operator splitting for adaptive radiation therapy with nonlinear health dynamics. Optim. Methods Softw. 37 (6) (2022)
Akshay Agrawal, Stephen P. Boyd, Deepak Narayanan, Fiodar Kazhamiaka, Matei Zaharia
Allocation of fungible resources via a fast, scalable price discovery method. Math. Program. Comput. 14 (3) (2022)
Guenther Walther, Alnur Ali, Xinyue Shen, Stephen P. Boyd
Confidence Bands for a Log-Concave Density. J. Comput. Graph. Stat. 31 (4) (2022)
Guillermo Angeris, Alex Evans, Tarun Chitra, Stephen P. Boyd
Optimal Routing for Constant Function Market Makers. EC (2022)
Bennet E. Meyers, Stephen P. Boyd
Signal Decomposition Using Masked Proximal Operators. CoRR (2022)
Nir Shlezinger, Yonina C. Eldar, Stephen P. Boyd
Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization. IEEE Access 10 (2022)
Nicholas Moehle, Stephen P. Boyd
A Certainty Equivalent Merton Problem. IEEE Control. Syst. Lett. 6 (2022)
Eric Luxenberg, Stephen P. Boyd, Mykel J. Kochenderfer, Misha van Beek, Wen Cao, Steven Diamond, Alex Ulitsky, Kunal Menda, Vidy Vairavamurthy
Strategic Asset Allocation with Illiquid Alternatives. CoRR (2022)
Gabriel Maher, Stephen P. Boyd, Mykel John Kochenderfer, Cristian Matache, Alex Ulitsky, Slava Yukhymuk, Leonid Kopman
A Light-Weight Multi-Objective Asynchronous Hyper-Parameter Optimizer. CoRR (2022)
Eric Luxenberg, Stephen P. Boyd, Misha van Beek, Wen Cao, Mykel J. Kochenderfer
Strategic Asset Allocation with Illiquid Alternatives. ICAIF (2022)
Shane T. Barratt, Stephen P. Boyd
Covariance Prediction via Convex Optimization. CoRR (2021)
Nicholas Moehle, Mykel J. Kochenderfer, Stephen P. Boyd, Andrew Ang
Tax-Aware Portfolio Construction via Convex Optimization. J. Optim. Theory Appl. 189 (2) (2021)
Charles W. Huang, Yong Yang, Neil Panjwani, Stephen P. Boyd, Lei Xing
Pareto Optimal Projection Search (POPS): Automated Radiation Therapy Treatment Planning by Direct Search of the Pareto Surface. IEEE Trans. Biomed. Eng. 68 (10) (2021)
Akshay Agrawal, Alnur Ali, Stephen P. Boyd
Minimum-Distortion Embedding. Found. Trends Mach. Learn. 14 (3) (2021)
Steven Diamond, Vincent Sitzmann, Frank D. Julca-Aguilar, Stephen P. Boyd, Gordon Wetzstein, Felix Heide
Dirty Pixels: Towards End-to-end Image Processing and Perception. ACM Trans. Graph. 40 (3) (2021)
Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd
Learning Convex Optimization Models. IEEE CAA J. Autom. Sinica 8 (8) (2021)
Junzi Zhang, Jongho Kim, Brendan O'Donoghue, Stephen P. Boyd
Sample Efficient Reinforcement Learning with REINFORCE. AAAI (2021)
Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
Optimal representative sample weighting. Stat. Comput. 31 (3) (2021)
Jonathan Tuck, Shane T. Barratt, Stephen P. Boyd
A Distributed Method for Fitting Laplacian Regularized Stratified Models. J. Mach. Learn. Res. 22 (2021)
Akshay Agrawal, Alnur Ali, Stephen P. Boyd
Minimum-Distortion Embedding. CoRR (2021)
Shane T. Barratt, Yining Dong, Stephen P. Boyd
Low Rank Forecasting. CoRR (2021)
Akshay Agrawal, Stephen P. Boyd, Deepak Narayanan, Fiodar Kazhamiaka, Matei Zaharia
Allocation of Fungible Resources via a Fast, Scalable Price Discovery Method. CoRR (2021)
Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd
Learning Convex Optimization Models. CoRR (2020)
Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint. L4DC (2020)
Akshay Agrawal, Stephen P. Boyd
Disciplined quasiconvex programming. Optim. Lett. 14 (7) (2020)
Junzi Zhang, Jongho Kim, Brendan O'Donoghue, Stephen P. Boyd
Sample Efficient Reinforcement Learning with REINFORCE. CoRR (2020)
Bartolomeo Stellato, Goran Banjac, Paul Goulart, Alberto Bemporad, Stephen P. Boyd
OSQP: an operator splitting solver for quadratic programs. Math. Program. Comput. 12 (4) (2020)
Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd, Bartolomeo Stellato
Learning Convex Optimization Control Policies. L4DC (2020)
Anqi Fu, Junzi Zhang, Stephen P. Boyd
Anderson Accelerated Douglas-Rachford Splitting. SIAM J. Sci. Comput. 42 (6) (2020)
Shane T. Barratt, Stephen P. Boyd
Fitting a Kalman Smoother to Data. ACC (2020)
Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. ICASSP (2020)
Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
Optimal Representative Sample Weighting. CoRR (2020)
Junzi Zhang, Brendan O'Donoghue, Stephen P. Boyd
Globally Convergent Type-I Anderson Acceleration for Nonsmooth Fixed-Point Iterations. SIAM J. Optim. 30 (4) (2020)
Mojtaba Tefagh, Stephen P. Boyd
SWIFTCORE: a tool for the context-specific reconstruction of genome-scale metabolic networks. BMC Bioinform. 21 (1) (2020)
Jonathan Tuck, Stephen P. Boyd
Fitting Laplacian Regularized Stratified Gaussian Models. CoRR (2020)
Reza Takapoui, Nicholas Moehle, Stephen P. Boyd, Alberto Bemporad
A simple effective heuristic for embedded mixed-integer quadratic programming. Int. J. Control 93 (1) (2020)
Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd
Minimizing a sum of clipped convex functions. Optim. Lett. 14 (8) (2020)
Jongho Kim, Youngsuk Park, John D. Fox, Stephen P. Boyd, William J. Dally
Optimal Operation of a Plug-in Hybrid Vehicle with Battery Thermal and Degradation Model. ACC (2020)
Jonathan Tuck, Stephen P. Boyd
Eigen-Stratified Models. CoRR (2020)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn
On the Convergence of Mirror Descent beyond Stochastic Convex Programming. SIAM J. Optim. 30 (1) (2020)
Peter Nystrup, Stephen P. Boyd, Erik Lindström, Henrik Madsen
Multi-period portfolio selection with drawdown control. Ann. Oper. Res. 282 (1-2) (2019)
Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd, Bartolomeo Stellato
Learning Convex Optimization Control Policies. CoRR (2019)
Shane T. Barratt, Stephen P. Boyd
Least Squares Auto-Tuning. CoRR (2019)
Akshay Agrawal, Stephen P. Boyd
Disciplined Quasiconvex Programming. CoRR (2019)
Jonathan Tuck, David Hallac, Stephen P. Boyd
Distributed majorization-minimization for Laplacian regularized problems. IEEE CAA J. Autom. Sinica 6 (1) (2019)
Akshay Agrawal, Steven Diamond, Stephen P. Boyd
Disciplined geometric programming. Optim. Lett. 13 (5) (2019)
Dave Deriso, Stephen P. Boyd
A General Optimization Framework for Dynamic Time Warping. CoRR (2019)
Nicholas Moehle, Xinyue Shen, Zhi-Quan Luo, Stephen P. Boyd
A Distributed Method for Optimal Capacity Reservation. J. Optim. Theory Appl. 182 (3) (2019)
Jonathan Tuck, Shane T. Barratt, Stephen P. Boyd
A Distributed Method for Fitting Laplacian Regularized Stratified Models. CoRR (2019)
Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter
Differentiable Convex Optimization Layers. CoRR (2019)
Baris Ungun, Lei Xing, Stephen P. Boyd
Real-Time Radiation Treatment Planning with Optimality Guarantees via Cluster and Bound Methods. INFORMS J. Comput. 31 (3) (2019)
David Hallac, Peter Nystrup, Stephen P. Boyd
Greedy Gaussian segmentation of multivariate time series. Adv. Data Anal. Classif. 13 (3) (2019)
Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter
Differentiable Convex Optimization Layers. NeurIPS (2019)
Goran Banjac, Paul Goulart, Bartolomeo Stellato, Stephen P. Boyd
Infeasibility Detection in the Alternating Direction Method of Multipliers for Convex Optimization. J. Optim. Theory Appl. 183 (2) (2019)
Enzo Busseti, Walaa M. Moursi, Stephen P. Boyd
Solution refinement at regular points of conic problems. Comput. Optim. Appl. 74 (3) (2019)
Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. CoRR (2019)
Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace From Position Data. IEEE Trans. Intell. Transp. Syst. 20 (9) (2019)
Akshay Agrawal, Robin Verschueren, Steven Diamond, Stephen P. Boyd
A rewriting system for convex optimization problems. J. Control. Decis. 5 (1) (2018)
David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec
Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data. IJCAI (2018)
Akshay Agrawal, Steven Diamond, Stephen P. Boyd
Disciplined Geometric Programming. CoRR (2018)
Qingyun Sun, Mengyuan Yan, David L. Donoho, Stephen P. Boyd
Convolutional Imputation of Matrix Networks. ICML (2018)
Alberto Bemporad, Valentina Breschi, Dario Piga, Stephen P. Boyd
Fitting jump models. Autom. 96 (2018)
Steven Diamond, Reza Takapoui, Stephen P. Boyd
A general system for heuristic minimization of convex functions over non-convex sets. Optim. Methods Softw. 33 (1) (2018)
Valentina Breschi, Alberto Bemporad, Dario Piga, Stephen P. Boyd
Prediction error methods in learning jump ARMAX models. CDC (2018)
Vincent Sitzmann, Steven Diamond, Yifan Peng, Xiong Dun, Stephen P. Boyd, Wolfgang Heidrich, Felix Heide, Gordon Wetzstein
End-to-end optimization of optics and image processing for achromatic extended depth of field and super-resolution imaging. ACM Trans. Graph. 37 (4) (2018)
Jaehyun Park, Stephen P. Boyd
A semidefinite programming method for integer convex quadratic minimization. Optim. Lett. 12 (3) (2018)
Ping Yin, Steven Diamond, Bill Lin, Stephen P. Boyd
Network Optimization for Unified Packet and Circuit Switched Networks. CoRR (2018)
Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data. CoRR (2018)
Bartolomeo Stellato, Vihangkumar V. Naik, Alberto Bemporad, Paul Goulart, Stephen P. Boyd
Embedded Mixed-Integer Quadratic optimization Using the OSQP Solver. ECC (2018)
David Hallac, Christopher Wong, Steven Diamond, Abhijit Sharang, Rok Sosic, Stephen P. Boyd, Jure Leskovec
SnapVX: A Network-Based Convex Optimization Solver. J. Mach. Learn. Res. 18 (2017)
Youngsuk Park, David Hallac, Stephen P. Boyd, Jure Leskovec
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields. AISTATS (2017)
Nan Zhang, Zhiqiang Yao, Yixian Liu, Stephen P. Boyd, Zhi-Quan Luo
Dynamic Resource Allocation for Energy Efficient Transmission in Digital Subscriber Lines. IEEE Trans. Signal Process. 65 (16) (2017)
David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. KDD (2017)
Akshay Agrawal, Robin Verschueren, Steven Diamond, Stephen P. Boyd
A Rewriting System for Convex Optimization Problems. CoRR (2017)
Stephen P. Boyd, Enzo Busseti, Steven Diamond, Ronald N. Kahn, Kwangmoo Koh, Peter Nystrup, Jan Speth
Multi-Period Trading via Convex Optimization. Found. Trends Optim. 3 (1) (2017)
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn
Mirror descent in non-convex stochastic programming. CoRR (2017)
Pontus Giselsson, Stephen P. Boyd
Linear Convergence and Metric Selection for Douglas-Rachford Splitting and ADMM. IEEE Trans. Autom. Control. 62 (2) (2017)
Nicholas Moehle, Xinyue Shen, Zhi-Quan Luo, Stephen P. Boyd
A Distributed Method for Optimal Capacity Reservation. CoRR (2017)
David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec
Network Inference via the Time-Varying Graphical Lasso. KDD (2017)
David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec
Network Inference via the Time-Varying Graphical Lasso. CoRR (2017)
Nicholas Boyd, Trevor Hastie, Stephen P. Boyd, Benjamin Recht, Michael I. Jordan
Saturating Splines and Feature Selection. J. Mach. Learn. Res. 18 (2017)
Steven Diamond, Vincent Sitzmann, Stephen P. Boyd, Gordon Wetzstein, Felix Heide
Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data. CoRR (2017)
Steven Diamond, Stephen P. Boyd
Stochastic Matrix-Free Equilibration. J. Optim. Theory Appl. 172 (2) (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Stephen P. Boyd