| JuMP: A modeling language for mathematical optimization I Dunning, J Huchette, M Lubin SIAM review 59 (2), 295-320, 2017 | 1849 | 2017 |
| Strong mixed-integer programming formulations for trained neural networks R Anderson, J Huchette, W Ma, C Tjandraatmadja, JP Vielma arXiv, arXiv: 1811.01988, 2020 | 273 | 2020 |
| Taming parallel I/O complexity with auto-tuning B Behzad, HVT Luu, J Huchette, S Byna, Prabhat, R Aydt, Q Koziol, M Snir Proceedings of the international conference on high performance computing …, 2013 | 149 | 2013 |
| 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 | 132 | 2023 |
| The convex relaxation barrier, revisited: Tightened single-neuron relaxations for neural network verification C Tjandraatmadja, R Anderson, J Huchette, W Ma, KK Patel, JP Vielma Advances in Neural Information Processing Systems 33, 21675-21686, 2020 | 82 | 2020 |
| Nonconvex piecewise linear functions: Advanced formulations and simple modeling tools J Huchette, JP Vielma Operations Research 71 (5), 1835-1856, 2023 | 62 | 2023 |
| Extended formulations in mixed integer conic quadratic programming JP Vielma, I Dunning, J Huchette, M Lubin Mathematical Programming Computation 9, 369-418, 2017 | 53 | 2017 |
| A combinatorial approach for small and strong formulations of disjunctive constraints J Huchette, JP Vielma Mathematics of Operations Research, 2019 | 37 | 2019 |
| Parallel algebraic modeling for stochastic optimization J Huchette, M Lubin, C Petra 2014 First Workshop for High Performance Technical Computing in Dynamic …, 2014 | 29 | 2014 |
| Sum-of-squares optimization in Julia B Legat, C Coey, R Deits, J Huchette, A Perry JuMP Developers Meetup/Workshop, 2017 | 26 | 2017 |
| When deep learning meets polyhedral theory: A survey J Huchette, G Muñoz, T Serra, C Tsay arXiv preprint arXiv:2305.00241, 2023 | 24 | 2023 |
| A framework for auto-tuning HDF5 applications B Behzad, J Huchette, HVT Luu, R Aydt, S Byna, Y Yao, Q Koziol, Prabhat Proceedings of the 22nd international symposium on High-performance parallel …, 2013 | 15 | 2013 |
| On efficient Hessian computation using the edge pushing algorithm in Julia CG Petra, F Qiang, M Lubin, J Huchette Optimization Methods and Software 33 (4-6), 1010-1029, 2018 | 11* | 2018 |
| Compact mixed-integer programming formulations in quadratic optimization B Beach, R Hildebrand, J Huchette Journal of Global Optimization 84 (4), 869-912, 2022 | 8* | 2022 |
| Strong mixed-integer formulations for the floor layout problem J Huchette, SS Dey, JP Vielma INFOR: Information Systems and Operational Research 56 (4), 392-433, 2018 | 8 | 2018 |
| A geometric way to build strong mixed-integer programming formulations J Huchette, JP Vielma Operations Research Letters 47 (6), 601-606, 2019 | 6 | 2019 |
| Auto-tuning of Parallel I/O Parameters for HDF5 Applications B Behzad, J Huchette, H Luu, R Aydt, Q Koziol, M Prabhat, S Byna, ... 2012 SC Companion: High Performance Computing, Networking Storage and …, 2012 | 6 | 2012 |
| Contextual reserve price optimization in auctions via mixed integer programming J Huchette, H Lu, H Esfandiari, V Mirrokni Advances in Neural Information Processing Systems 33, 1287-1297, 2020 | 5 | 2020 |
| Prabhat, Ruth Aydt, Quincey Koziol, and Marc Snir. 2013. Taming parallel I/O complexity with auto-tuning B Behzad, HVT Luu, J Huchette, S Byna Proceedings of 2013 International Conference for High Performance Computing …, 2013 | 5 | 2013 |
| A mixed-integer branching approach for very small formulations of disjunctive constraints J Huchette, JP Vielma arXiv preprint arXiv:1709.10132, 2017 | 3 | 2017 |
Juan Pablo VielmaResearch Scientist, Google在 google.com 的电子邮件经过验证
