Zobrazeno 1 - 10
of 101
pro vyhledávání: '"Lubin, Miles"'
Autor:
Lubin, Miles, Dowson, Oscar, Garcia, Joaquim Dias, Huchette, Joey, Legat, Benoît, Vielma, Juan Pablo
JuMP is an algebraic modeling language embedded in the Julia programming language. JuMP allows users to model optimization problems of a variety of kinds, including linear programming, integer programming, conic optimization, semidefinite programming
Externí odkaz:
http://arxiv.org/abs/2206.03866
Autor:
Gasse, Maxime, Cappart, Quentin, Charfreitag, Jonas, Charlin, Laurent, Chételat, Didier, Chmiela, Antonia, Dumouchelle, Justin, Gleixner, Ambros, Kazachkov, Aleksandr M., Khalil, Elias, Lichocki, Pawel, Lodi, Andrea, Lubin, Miles, Maddison, Chris J., Morris, Christopher, Papageorgiou, Dimitri J., Parjadis, Augustin, Pokutta, Sebastian, Prouvost, Antoine, Scavuzzo, Lara, Zarpellon, Giulia, Yang, Linxin, Lai, Sha, Wang, Akang, Luo, Xiaodong, Zhou, Xiang, Huang, Haohan, Shao, Shengcheng, Zhu, Yuanming, Zhang, Dong, Quan, Tao, Cao, Zixuan, Xu, Yang, Huang, Zhewei, Zhou, Shuchang, Binbin, Chen, Minggui, He, Hao, Hao, Zhiyu, Zhang, Zhiwu, An, Kun, Mao
Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolation, ignoring that they often stem from related data distributions in pr
Externí odkaz:
http://arxiv.org/abs/2203.02433
Autor:
Doudchenko, Nick, Khosravi, Khashayar, Pouget-Abadie, Jean, Lahaie, Sebastien, Lubin, Miles, Mirrokni, Vahab, Spiess, Jann, Imbens, Guido
We investigate the optimal design of experimental studies that have pre-treatment outcome data available. The average treatment effect is estimated as the difference between the weighted average outcomes of the treated and control units. A number of
Externí odkaz:
http://arxiv.org/abs/2112.00278
Autor:
Applegate, David, Díaz, Mateo, Hinder, Oliver, Lu, Haihao, Lubin, Miles, O'Donoghue, Brendan, Schudy, Warren
We present PDLP, a practical first-order method for linear programming (LP) that can solve to the high levels of accuracy that are expected in traditional LP applications. In addition, it can scale to very large problems because its core operation is
Externí odkaz:
http://arxiv.org/abs/2106.04756
First-order primal-dual methods are appealing for their low memory overhead, fast iterations, and effective parallelization. However, they are often slow at finding high accuracy solutions, which creates a barrier to their use in traditional linear p
Externí odkaz:
http://arxiv.org/abs/2105.12715
Mixed-integer convex representable (MICP-R) sets are those sets that can be represented exactly through a mixed-integer convex programming formulation. Following up on recent work by Lubin et al. (2017, 2020) we investigate structural geometric prope
Externí odkaz:
http://arxiv.org/abs/2103.03379
We study the problem of detecting infeasibility of large-scale linear programming problems using the primal-dual hybrid gradient method (PDHG) of Chambolle and Pock (2011). The literature on PDHG has mostly focused on settings where the problem at ha
Externí odkaz:
http://arxiv.org/abs/2102.04592
Autor:
Zadik, Ilias1 (AUTHOR), Lubin, Miles2 (AUTHOR), Vielma, Juan Pablo3 (AUTHOR) jvielma@google.com
Publikováno v:
Mathematical Programming. Mar2024, Vol. 204 Issue 1/2, p739-752. 14p.
Autor:
Hinder, Oliver, Lubin, Miles
We provide a simple and generic adaptive restart scheme for convex optimization that is able to achieve worst-case bounds matching (up to constant multiplicative factors) optimal restart schemes that require knowledge of problem specific constants. T
Externí odkaz:
http://arxiv.org/abs/2006.08484
We introduce MathOptInterface, an abstract data structure for representing mathematical optimization problems based on combining pre-defined functions and sets. MathOptInterface is significantly more general than existing data structures in the liter
Externí odkaz:
http://arxiv.org/abs/2002.03447