| JuMP: A modeling language for mathematical optimization I Dunning, J Huchette, M Lubin SIAM Review 59 (2), 295-320, 2017 | 1974 | 2017 |
| Forward-Mode Automatic Differentiation in Julia J Revels, M Lubin, T Papamarkou arXiv preprint arXiv:1607.07892, 2016 | 517 | 2016 |
| Computing in operations research using Julia M Lubin, I Dunning INFORMS Journal on Computing 27 (2), 238-248, 2015 | 417 | 2015 |
| Powermodels. jl: An open-source framework for exploring power flow formulations C Coffrin, R Bent, K Sundar, Y Ng, M Lubin 2018 Power Systems Computation Conference (PSCC), 1-8, 2018 | 347 | 2018 |
| A robust approach to chance constrained optimal power flow with renewable generation M Lubin, Y Dvorkin, S Backhaus IEEE Transactions on Power Systems 31 (5), 3840-3849, 2015 | 294 | 2015 |
| JuMP 1.0: Recent improvements to a modeling language for mathematical optimization M Lubin, O Dowson, JD Garcia, J Huchette, B Legat, JP Vielma Mathematical Programming Computation 15 (3), 581-589, 2023 | 263 | 2023 |
| An augmented incomplete factorization approach for computing the Schur complement in stochastic optimization CG Petra, O Schenk, M Lubin, K Gärtner SIAM Journal on Scientific Computing 36 (2), C139-C162, 2014 | 213 | 2014 |
| Reformulation versus cutting-planes for robust optimization: A computational study D Bertsimas, I Dunning, M Lubin Computational Management Science 13, 195-217, 2016 | 152 | 2016 |
| Uncertainty sets for wind power generation Y Dvorkin, M Lubin, S Backhaus, M Chertkov IEEE Transactions on Power Systems 31 (4), 3326-3327, 2015 | 111 | 2015 |
| Reinforced genetic algorithm learning for optimizing computation graphs A Paliwal, F Gimeno, V Nair, Y Li, M Lubin, P Kohli, O Vinyals International Conference on Learning Representations, 2020 | 97* | 2020 |
| MathOptInterface: a data structure for mathematical optimization problems B Legat, O Dowson, JD Garcia, M Lubin INFORMS Journal on Computing 34 (2), 672-689, 2022 | 90 | 2022 |
| On parallelizing dual decomposition in stochastic integer programming M Lubin, K Martin, CG Petra, B Sandıkçı Operations Research Letters 41 (3), 252-258, 2013 | 90 | 2013 |
| Practical large-scale linear programming using primal-dual hybrid gradient D Applegate, M Díaz, O Hinder, H Lu, M Lubin, B O'Donoghue, W Schudy Advances in Neural Information Processing Systems 34, 20243-20257, 2021 | 86 | 2021 |
| Polyhedral approximation in mixed-integer convex optimization M Lubin, E Yamangil, R Bent, JP Vielma Mathematical Programming 172, 139-168, 2018 | 82 | 2018 |
| Outer approximation with conic certificates for mixed-integer convex problems C Coey, M Lubin, JP Vielma Mathematical Programming Computation 12 (2), 249-293, 2020 | 80 | 2020 |
| Chance constraints for improving the security of AC optimal power flow M Lubin, Y Dvorkin, L Roald IEEE Transactions on Power Systems 34 (3), 1908-1917, 2019 | 80 | 2019 |
| Scalable stochastic optimization of complex energy systems M Lubin, CG Petra, M Anitescu, V Zavala Proceedings of 2011 International Conference for High Performance Computing …, 2011 | 79 | 2011 |
| Extended formulations in mixed-integer convex programming M Lubin, E Yamangil, R Bent, JP Vielma Integer Programming and Combinatorial Optimization: 18th International …, 2016 | 69 | 2016 |
| Faster first-order primal-dual methods for linear programming using restarts and sharpness D Applegate, O Hinder, H Lu, M Lubin Mathematical Programming 201 (1), 133-184, 2023 | 59 | 2023 |
| Extended formulations in mixed integer conic quadratic programming JP Vielma, I Dunning, J Huchette, M Lubin Mathematical Programming Computation 9, 369-418, 2017 | 54 | 2017 |
Iain DunningDeepMindVerified email at google.com