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ORCIDStephen P. Boyd
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- affiliation: Stanford University, USA
- award (2017): IEEE James H. Mulligan, Jr. Education Medal
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2020 – today
- 2020
[j110]Mojtaba Tefagh
, Stephen P. Boyd:
SWIFTCORE: a tool for the context-specific reconstruction of genome-scale metabolic networks. BMC Bioinform. 21(1): 140 (2020)- [j109]Reza Takapoui, Nicholas Moehle, Stephen P. Boyd, Alberto Bemporad:
A simple effective heuristic for embedded mixed-integer quadratic programming. Int. J. Control 93(1): 2-12 (2020) - [j108]Akshay Agrawal, Stephen P. Boyd:
Disciplined quasiconvex programming. Optim. Lett. 14(7): 1643-1657 (2020) - [j107]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): 687-716 (2020) - [c95]Shane T. Barratt, Stephen P. Boyd:
Fitting a Kalman Smoother to Data. ACC 2020: 1526-1531 - [c94]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: 3083-3090 - [c93]Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah:
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. ICASSP 2020: 3597-3601 - [i33]Jonathan Tuck, Stephen P. Boyd:
Eigen-Stratified Models. CoRR abs/2001.10389 (2020) - [i32]Jonathan Tuck, Stephen P. Boyd:
Fitting Laplacian Regularized Stratified Gaussian Models. CoRR abs/2005.01752 (2020) - [i31]Shane T. Barratt, Guillermo Angeris, Stephen P. Boyd:
Optimal Representative Sample Weighting. CoRR abs/2005.09065 (2020) - [i30]Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd:
Learning Convex Optimization Models. CoRR abs/2006.04248 (2020)
2010 – 2019
- 2019
- [j106]David Hallac, Peter Nystrup, Stephen P. Boyd:
Greedy Gaussian segmentation of multivariate time series. Adv. Data Anal. Classif. 13(3): 727-751 (2019) - [j105]Peter Nystrup, Stephen P. Boyd, Erik Lindström, Henrik Madsen:
Multi-period portfolio selection with drawdown control. Ann. Oper. Res. 282(1-2): 245-271 (2019) - [j104]Enzo Busseti, Walaa M. Moursi, Stephen P. Boyd:
Solution refinement at regular points of conic problems. Comput. Optim. Appl. 74(3): 627-643 (2019) - [j103]Jonathan Tuck, David Hallac, Stephen P. Boyd:
Distributed majorization-minimization for Laplacian regularized problems. IEEE CAA J. Autom. Sinica 6(1): 45-52 (2019) - [j102]Nicholas Moehle, Xinyue Shen, Zhi-Quan Luo, Stephen P. Boyd:
A Distributed Method for Optimal Capacity Reservation. J. Optim. Theory Appl. 182(3): 1130-1149 (2019) - [j101]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): 490-519 (2019) - [j100]Akshay Agrawal, Steven Diamond, Stephen P. Boyd:
Disciplined geometric programming. Optim. Lett. 13(5): 961-976 (2019) - [j99]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): 3536-3545 (2019) - [c92]Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter:
Differentiable Convex Optimization Layers. NeurIPS 2019: 9558-9570 - [i29]Shane T. Barratt, Stephen P. Boyd:
Least Squares Auto-Tuning. CoRR abs/1904.05460 (2019) - [i28]Jonathan Tuck, Shane T. Barratt, Stephen P. Boyd:
A Distributed Method for Fitting Laplacian Regularized Stratified Models. CoRR abs/1904.12017 (2019) - [i27]Akshay Agrawal, Stephen P. Boyd:
Disciplined Quasiconvex Programming. CoRR abs/1905.00562 (2019) - [i26]Dave Deriso, Stephen P. Boyd:
A General Optimization Framework for Dynamic Time Warping. CoRR abs/1905.12893 (2019) - [i25]Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah:
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. CoRR abs/1910.07056 (2019) - [i24]Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter:
Differentiable Convex Optimization Layers. CoRR abs/1910.12430 (2019) - [i23]Akshay Agrawal, Shane T. Barratt, Stephen P. Boyd, Bartolomeo Stellato:
Learning Convex Optimization Control Policies. CoRR abs/1912.09529 (2019) - 2018
- [j98]Alberto Bemporad, Valentina Breschi, Dario Piga, Stephen P. Boyd:
Fitting jump models. Autom. 96: 11-21 (2018) - [j97]Jaehyun Park, Stephen P. Boyd:
A semidefinite programming method for integer convex quadratic minimization. Optim. Lett. 12(3): 499-518 (2018) - [j96]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): 165-193 (2018) - [j95]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): 114:1-114:13 (2018) - [c91]Valentina Breschi, Alberto Bemporad, Dario Piga, Stephen P. Boyd:
Prediction error methods in learning jump ARMAX models. CDC 2018: 2247-2252 - [c90]Bartolomeo Stellato, Vihangkumar V. Naik, Alberto Bemporad, Paul Goulart, Stephen P. Boyd:
Embedded Mixed-Integer Quadratic optimization Using the OSQP Solver. ECC 2018: 1536-1541 - [c89]Qingyun Sun, Mengyuan Yan, David L. Donoho, Stephen P. Boyd:
Convolutional Imputation of Matrix Networks. ICML 2018: 4825-4834 - [c88]David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec:
Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data. IJCAI 2018: 5254-5258 - [i22]Ping Yin, Steven Diamond, Bill Lin, Stephen P. Boyd:
Network Optimization for Unified Packet and Circuit Switched Networks. CoRR abs/1808.00586 (2018) - [i21]Shane T. Barratt, Mykel J. Kochenderfer, Stephen P. Boyd:
Learning Probabilistic Trajectory Models of Aircraft in Terminal Airspace from Position Data. CoRR abs/1810.09568 (2018) - [i20]Akshay Agrawal, Steven Diamond, Stephen P. Boyd:
Disciplined Geometric Programming. CoRR abs/1812.04074 (2018) - 2017
- [j94]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): 1-76 (2017) - [j93]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: 4:1-4:5 (2017) - [j92]Nicholas Boyd, Trevor Hastie, Stephen P. Boyd, Benjamin Recht, Michael I. Jordan:
Saturating Splines and Feature Selection. J. Mach. Learn. Res. 18: 197:1-197:32 (2017) - [j91]Steven Diamond, Stephen P. Boyd:
Stochastic Matrix-Free Equilibration. J. Optim. Theory Appl. 172(2): 436-454 (2017) - [j90]Pontus Giselsson, Stephen P. Boyd:
Linear Convergence and Metric Selection for Douglas-Rachford Splitting and ADMM. IEEE Trans. Autom. Control. 62(2): 532-544 (2017) - [j89]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): 4353-4366 (2017) - [c87]Youngsuk Park, David Hallac, Stephen P. Boyd, Jure Leskovec:
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields. AISTATS 2017: 1302-1310 - [c86]Matt Wytock, Nicholas Moehle, Stephen P. Boyd:
Dynamic energy management with scenario-based robust MPC. ACC 2017: 2042-2047 - [c85]Goran Banjac, Bartolomeo Stellato, Nicholas Moehle, Paul Goulart, Alberto Bemporad, Stephen P. Boyd:
Embedded code generation using the OSQP solver. CDC 2017: 1906-1911 - [c84]David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec:
Network Inference via the Time-Varying Graphical Lasso. KDD 2017: 205-213 - [c83]David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec:
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. KDD 2017: 215-223 - [c82]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn:
Stochastic Mirror Descent in Variationally Coherent Optimization Problems. NIPS 2017: 7040-7049 - [i19]Steven Diamond, Vincent Sitzmann, Stephen P. Boyd, Gordon Wetzstein, Felix Heide:
Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data. CoRR abs/1701.06487 (2017) - [i18]David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec:
Network Inference via the Time-Varying Graphical Lasso. CoRR abs/1703.01958 (2017) - [i17]Nicholas Moehle, Xinyue Shen, Zhi-Quan Luo, Stephen P. Boyd:
A Distributed Method for Optimal Capacity Reservation. CoRR abs/1705.00677 (2017) - [i16]David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec:
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. CoRR abs/1706.03161 (2017) - [i15]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Stephen P. Boyd, Peter W. Glynn:
Mirror descent in non-convex stochastic programming. CoRR abs/1706.05681 (2017) - [i14]Akshay Agrawal, Robin Verschueren, Steven Diamond, Stephen P. Boyd:
A Rewriting System for Convex Optimization Problems. CoRR abs/1709.04494 (2017) - [i13]Alberto Bemporad, Valentina Breschi, Dario Piga, Stephen P. Boyd:
Fitting Jump Models. CoRR abs/1711.09220 (2017) - 2016
- [j88]Madeleine Udell, Stephen P. Boyd:
Bounding duality gap for separable problems with linear constraints. Comput. Optim. Appl. 64(2): 355-378 (2016) - [j87]Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd:
Generalized Low Rank Models. Found. Trends Mach. Learn. 9(1): 1-118 (2016) - [j86]Steven Diamond, Stephen P. Boyd:
CVXPY: A Python-Embedded Modeling Language for Convex Optimization. J. Mach. Learn. Res. 17: 83:1-83:5 (2016) - [j85]Weijie Su, Stephen P. Boyd, Emmanuel J. Candès:
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights. J. Mach. Learn. Res. 17: 153:1-153:43 (2016) - [j84]Brendan O'Donoghue, Eric Chu, Neal Parikh, Stephen P. Boyd:
Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding. J. Optim. Theory Appl. 169(3): 1042-1068 (2016) - [j83]Thomas Lipp, Stephen P. Boyd:
Antagonistic control. Syst. Control. Lett. 98: 44-48 (2016) - [c81]Nicholas Moehle, Stephen P. Boyd:
Optimal current waveforms for switched-reluctance motors. CCA 2016: 1129-1136 - [c80]Reza Takapoui, Nicholas Moehle, Stephen P. Boyd, Alberto Bemporad:
A simple effective heuristic for embedded mixed-integer quadratic programming. ACC 2016: 5619-5625 - [c79]Xinyue Shen, Steven Diamond, Yuantao Gu, Stephen P. Boyd:
Disciplined convex-concave programming. CDC 2016: 1009-1014 - [c78]Pontus Giselsson, Mattias Fält, Stephen P. Boyd:
Line search for averaged operator iteration. CDC 2016: 1015-1022 - [c77]Nicholas Moehle, Stephen P. Boyd:
Maximum torque-per-current control of induction motors via semidefinite programming. CDC 2016: 1920-1925 - [c76]Nan Zhang, Zhiqiang Yao, Yixian Liu, Stephen P. Boyd, Zhi-Quan Luo:
Optimal Resource Allocation for Energy Efficient Transmission in DSL. GLOBECOM 2016: 1-6 - [c75]Matt Wytock, Steven Diamond, Felix Heide, Stephen P. Boyd:
A New Architecture for Optimization Modeling Frameworks. PyHPC@SC 2016: 36-44 - [i12]Nicholas Moehle, Stephen P. Boyd:
Optimal Current Waveforms for Switched-Reluctance Motors. CoRR abs/1601.03768 (2016) - [i11]Qingyun Sun, Mengyuan Yan, Stephen P. Boyd:
Convolutional Imputation of Matrix Network. CoRR abs/1606.00925 (2016) - [i10]Reza Takapoui, Stephen P. Boyd:
Linear Programming Heuristics for the Graph Isomorphism Problem. CoRR abs/1611.00711 (2016) - 2015
- [j82]Pontus Giselsson, Stephen P. Boyd:
Metric selection in fast dual forward-backward splitting. Autom. 62: 1-10 (2015) - [j81]Ernest K. Ryu, Stephen P. Boyd:
Extensions of Gauss Quadrature Via Linear Programming. Found. Comput. Math. 15(4): 953-971 (2015) - [j80]Nicholas Moehle, Stephen P. Boyd:
Optimal current waveforms for brushless permanent magnet motors. Int. J. Control 88(7): 1389-1399 (2015) - [j79]Nicholas Moehle, Stephen P. Boyd:
A perspective-based convex relaxation for switched-affine optimal control. Syst. Control. Lett. 86: 34-40 (2015) - [j78]Lipeng Ning, Tryphon T. Georgiou, Allen R. Tannenbaum, Stephen P. Boyd:
Linear Models Based on Noisy Data and the Frisch Scheme. SIAM Rev. 57(2): 167-197 (2015) - [c74]Saahil Shenoy, Dimitry M. Gorinevsky, Stephen P. Boyd:
Non-parametric regression modeling for stochastic optimization of power grid load forecast. ACC 2015: 1010-1015 - [c73]Steven Diamond, Stephen P. Boyd:
Convex Optimization with Abstract Linear Operators. ICCV 2015: 675-683 - [c72]David Hallac, Jure Leskovec, Stephen P. Boyd:
Network Lasso: Clustering and Optimization in Large Graphs. KDD 2015: 387-396 - [c71]Alnur Ali, J. Zico Kolter, Steven Diamond, Stephen P. Boyd:
Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization. UAI 2015: 62-71 - [i9]Jaehyun Park, Stephen P. Boyd:
A Semidefinite Programming Method for Integer Convex Quadratic Minimization. CoRR abs/1504.07672 (2015) - [i8]David Hallac, Jure Leskovec, Stephen P. Boyd:
Network Lasso: Clustering and Optimization in Large Graphs. CoRR abs/1507.00280 (2015) - [i7]David Hallac, Christopher Wong, Steven Diamond, Rok Sosic, Stephen P. Boyd, Jure Leskovec:
SnapVX: A Network-Based Convex Optimization Solver. CoRR abs/1509.06397 (2015) - 2014
- [b2]Stephen P. Boyd, Lieven Vandenberghe:
Convex Optimization. Cambridge University Press 2014, ISBN 978-0-521-83378-3 - [j77]Stephen P. Boyd, Mark T. Müller, Brendan O'Donoghue, Yang Wang:
Performance Bounds and Suboptimal Policies for Multi-Period Investment. Found. Trends Optim. 1(1): 1-72 (2014) - [j76]Matt Kraning, Eric Chu, Javad Lavaei, Stephen P. Boyd:
Dynamic Network Energy Management via Proximal Message Passing. Found. Trends Optim. 1(2): 73-126 (2014) - [j75]Neal Parikh, Stephen P. Boyd:
Proximal Algorithms. Found. Trends Optim. 1(3): 127-239 (2014) - [j74]Thomas Lipp, Stephen P. Boyd:
Minimum-time speed optimisation over a fixed path. Int. J. Control 87(6): 1297-1311 (2014) - [j73]Neal Parikh, Stephen P. Boyd:
Block splitting for distributed optimization. Math. Program. Comput. 6(1): 77-102 (2014) - [j72]Aditya G. Parameswaran, Stephen P. Boyd, Hector Garcia-Molina, Ashish Gupta, Neoklis Polyzotis, Jennifer Widom:
Optimal Crowd-Powered Rating and Filtering Algorithms. Proc. VLDB Endow. 7(9): 685-696 (2014) - [c70]Pontus Giselsson, Stephen P. Boyd:
Diagonal scaling in Douglas-Rachford splitting and ADMM. CDC 2014: 5033-5039 - [c69]Pontus Giselsson, Stephen P. Boyd:
Preconditioning in fast dual gradient methods. CDC 2014: 5040-5045 - [c68]Pontus Giselsson, Stephen P. Boyd:
Monotonicity and restart in fast gradient methods. CDC 2014: 5058-5063 - [c67]Stephen P. Boyd:
Plenary talk: Performance bounds and suboptimal policies for multi-period investment. MED 2014: 1 - [c66]Weijie Su, Stephen P. Boyd, Emmanuel J. Candès:
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights. NIPS 2014: 2510-2518 - [c65]Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd:
Convex optimization in Julia. HPTCDL@SC 2014: 18-28 - [i6]Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen P. Boyd:
Generalized Low Rank Models. CoRR abs/1410.0342 (2014) - [i5]Madeleine Udell, Karanveer Mohan, David Zeng, Jenny Hong, Steven Diamond, Stephen P. Boyd:
Convex Optimization in Julia. CoRR abs/1410.4821 (2014) - 2013
- [j71]Tobias Gybel Hovgaard, Stephen P. Boyd, Lars Finn Sloth Larsen, John Bagterp Jørgensen:
Nonconvex model predictive control for commercial refrigeration. Int. J. Control 86(8): 1349-1366 (2013) - [j70]Vanya Van Belle, Patrick Neven, Vernon Harvey, Sabine Van Huffel, Johan A. K. Suykens, Stephen P. Boyd:
Risk group detection and survival function estimation for interval coded survival methods. Neurocomputing 112: 200-210 (2013) - [j69]Brendan O'Donoghue, Giorgos Stathopoulos, Stephen P. Boyd:
A Splitting Method for Optimal Control. IEEE Trans. Control. Syst. Technol. 21(6): 2432-2442 (2013) - [c64]Eric Chu, Neal Parikh, Alexander Domahidi, Stephen P. Boyd:
Code generation for embedded second-order cone programming. ECC 2013: 1547-1552 - [c63]Alexander Domahidi, Eric Chu, Stephen P. Boyd:
ECOS: An SOCP solver for embedded systems. ECC 2013: 3071-3076 - [c62]Brendan O'Donoghue, Yang Wang, Stephen P. Boyd:
Iterated approximate value functions. ECC 2013: 3882-3888 - [c61]Tobias Gybel Hovgaard, Lars Finn Sloth Larsen, John Bagterp Jørgensen, Stephen P. Boyd:
MPC for wind power gradients - utilizing forecasts, rotor inertia, and central energy storage. ECC 2013: 4071-4076 - [c60]Martin Hast, Karl Johan Åström, Bo Bernhardsson, Stephen P. Boyd:
PID design by convex-concave optimization. ECC 2013: 4460-4465 - [i4]Lipeng Ning, Tryphon T. Georgiou, Allen R. Tannenbaum, Stephen P. Boyd:
Linear models based on noisy data and the Frisch scheme. CoRR abs/1304.3877 (2013) - 2012
- [j68]Henrik Ohlsson, Fredrik Gustafsson, Lennart Ljung, Stephen P. Boyd:
Smoothed state estimates under abrupt changes using sum-of-norms regularization. Autom. 48(4): 595-605 (2012) - [c59]Eric Chu, Arezou Keshavarz, Dimitry M. Gorinevsky, Stephen P. Boyd:
Moving horizon estimation for staged QP problems. CDC 2012: 3177-3182 - [c58]Vanya Van Belle, Sabine Van Huffel, Johan A. K. Suykens, Stephen P. Boyd:
Interval coded scoring systems for survival analysis. ESANN 2012 - [c57]Stephen P. Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic:
Accuracy at the Top. NIPS 2012: 962-970 - [i3]Matt Kraning, Eric Chu, Javad Lavaei, Stephen P. Boyd:
Message Passing for Dynamic Network Energy Management. CoRR abs/1204.1106 (2012) - 2011
- [j67]Michael M. Zavlanos, A. Agung Julius, Stephen P. Boyd, George J. Pappas:
Inferring stable genetic networks from steady-state data. Autom. 47(6): 1113-1122 (2011) - [j66]Stephen P. Boyd, Neal Parikh, Eric Chu, Borja Peleato, Jonathan Eckstein:
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers. Found. Trends Mach. Learn. 3(1): 1-122 (2011) - [j65]Evelyn Mintarno, Joëlle Skaf, Rui Zheng, Jyothi Velamala, Yu Cao, Stephen P. Boyd, Robert W. Dutton, Subhasish Mitra:
Self-Tuning for Maximized Lifetime Energy-Efficiency in the Presence of Circuit Aging. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 30(5): 760-773 (2011) - [j64]Yang Wang, Stephen P. Boyd:
Fast Evaluation of Quadratic Control-Lyapunov Policy. IEEE Trans. Control. Syst. Technol. 19(4): 939-946 (2011) - [c56]Mohsen Soltani, Rafael Wisniewski, Per Brath, Stephen P. Boyd:
Load reduction of wind turbines using receding horizon control. CCA 2011: 852-857 - [c55]Benjamin Biegel, Morten Juelsgaard, Matt Kraning, Stephen P. Boyd, Jakob Stoustrup:
Wind turbine pitch optimization. CCA 2011: 1327-1334 - [c54]Arezou Keshavarz, Yang Wang, Stephen P. Boyd:
Imputing a convex objective function. ISIC 2011: 613-619 - [c53]Brendan O'Donoghue, Yang Wang, Stephen P. Boyd:
Min-max approximate dynamic programming. CACSD 2011: 424-431 - [c52]Stephen P. Boyd:
Convex optimization: from embedded real-time to large-scale distributed. KDD 2011: 1 - 2010
- [j63]Henrik Ohlsson, Lennart Ljung, Stephen P. Boyd:
Segmentation of ARX-models using sum-of-norms regularization. Autom. 46(6): 1107-1111 (2010) - [j62]Ekine Akuiyibo, Stephen P. Boyd:
Adaptive Modulation with Smoothed Flow Utility. EURASIP J. Wirel. Commun. Netw. 2010 (2010) - [j61]Argyrios Zymnis, Stephen P. Boyd, Dimitry M. Gorinevsky:
Mixed linear system estimation and identification. Signal Process. 90(3): 966-971 (2010) - [j60]Argyrios Zymnis, Stephen P. Boyd, Emmanuel J. Candès:
Compressed Sensing With Quantized Measurements. IEEE Signal Process. Lett. 17(2): 149-152 (2010) - [j59]John Mattingley, Stephen P. Boyd:
Real-Time Convex Optimization in Signal Processing. IEEE Signal Process. Mag. 27(3): 50-61 (2010) - [j58]