| OSQP: An operator splitting solver for quadratic programs B Stellato, G Banjac, P Goulart, A Bemporad, S Boyd Mathematical Programming Computation 12 (4), 637-672, 2020 | 1105 | 2020 |
| Infeasibility detection in the alternating direction method of multipliers for convex optimization G Banjac, P Goulart, B Stellato, S Boyd Journal of Optimization Theory and Applications 183 (2), 490–519, 2019 | 103 | 2019 |
| Embedded code generation using the OSQP solver G Banjac, B Stellato, N Moehle, P Goulart, A Bemporad, S Boyd 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 1906-1911, 2017 | 73 | 2017 |
| GPU acceleration of ADMM for large-scale quadratic programming M Schubiger, G Banjac, J Lygeros Journal of Parallel and Distributed Computing 144, 55-67, 2020 | 45 | 2020 |
| Decentralized resource allocation via dual consensus ADMM G Banjac, F Rey, P Goulart, J Lygeros 2019 American Control Conference (ACC), 2789-2794, 2019 | 27 | 2019 |
| Tight global linear convergence rate bounds for operator splitting methods G Banjac, PJ Goulart IEEE Transactions on Automatic Control 63 (12), 4126-4139, 2018 | 27 | 2018 |
| Load forecast of a university building for application in microgrid power flow optimization M Gulin, M Vašak, G Banjac, T Tomiša 2014 IEEE International Energy Conference (ENERGYCON), 1223-1227, 2014 | 26 | 2014 |
| Accelerating quadratic optimization with reinforcement learning J Ichnowski, P Jain, B Stellato, G Banjac, M Luo, F Borrelli, JE Gonzalez, ... Advances in Neural Information Processing Systems 34, 21043-21055, 2021 | 23 | 2021 |
| A Data-Driven Policy Iteration Scheme based on Linear Programming G Banjac, J Lygeros IEEE Conference on Decision and Control, 2019 | 20 | 2019 |
| Adaptable urban water demand prediction system G Banjac, M Vašak, M Baotić Water Science and Technology: Water Supply 15 (5), 958-964, 2015 | 16 | 2015 |
| Dynamic day-ahead water pricing based on smart metering and demand prediction M Vašak, G Banjac, M Baotić, J Matuško Procedia Engineering 89, 1031-1036, 2014 | 16 | 2014 |
| On the convergence of a regularized Jacobi algorithm for convex optimization G Banjac, K Margellos, PJ Goulart IEEE Transactions on Automatic Control 63 (4), 1113-1119, 2018 | 15 | 2018 |
| Water use disaggregation based on classification of feature vectors extracted from smart meter data M Vašak, G Banjac, H Novak Procedia Engineering 119, 1381-1390, 2015 | 12 | 2015 |
| A novel approach for solving convex problems with cardinality constraints G Banjac, PJ Goulart IFAC-PapersOnLine 50 (1), 13182-13187, 2017 | 10 | 2017 |
| Embedded code generation with CVXPY M Schaller, G Banjac, S Diamond, A Agrawal, B Stellato, S Boyd IEEE Control Systems Letters 6, 2653-2658, 2022 | 9 | 2022 |
| On the asymptotic behavior of the Douglas-Rachford and proximal-point algorithms for convex optimization G Banjac, J Lygeros Optimization Letters 15 (8), 2719-2732, 2021 | 9 | 2021 |
| Distributed model predictive control with reconfigurable terminal ingredients for reference tracking A Aboudonia, A Eichler, F Cordiano, G Banjac, J Lygeros IEEE transactions on automatic control 67 (11), 6263-6270, 2021 | 8 | 2021 |
| On the minimal displacement vector of the Douglas-Rachford operator G Banjac Operations Research Letters 49 (2), 197-200, 2021 | 8 | 2021 |
| Efficient performance bounds for primal-dual reinforcement learning from demonstrations A Kamoutsi, G Banjac, J Lygeros International Conference on Machine Learning, 5257-5268, 2021 | 7 | 2021 |
| Global linear convergence in operator splitting methods G Banjac, PJ Goulart 2016 IEEE 55th Conference on Decision and Control (CDC), 233-238, 2016 | 5 | 2016 |
Paul GoulartUniversity of OxfordVerified email at eng.ox.ac.uk
