Scalable stochastic optimization of complex energy systems. - Miles Lubin; Cosmin G. Petra; Mihai Anitescu; Victor M. Zavala (SC, 2011)

The parallel solution of dense saddle-point linear systems arising in stochastic programming. - Miles Lubin; Cosmin G. Petra; Mihai Anitescu (Optim. Methods Softw., 2012)

Parallel distributed-memory simplex for large-scale stochastic LP problems. - Miles Lubin; J. A. Julian Hall; Cosmin G. Petra; Mihai Anitescu (Comput. Optim. Appl., 2013)

On parallelizing dual decomposition in stochastic integer programming. - Miles Lubin; R. Kipp Martin; Cosmin G. Petra; Burhaneddin Sandikçi (Oper. Res. Lett., 2013)

Parallel algebraic modeling for stochastic optimization. - Joey Huchette; Miles Lubin; Cosmin G. Petra (HPTCDL@SC, 2014)

An Augmented Incomplete Factorization Approach for Computing the Schur Complement in Stochastic Optimization. - Cosmin G. Petra; Olaf Schenk; Miles Lubin; Klaus Gärtner (SIAM J. Sci. Comput., 2014)

Computing in Operations Research Using Julia. - Miles Lubin; Iain Dunning (INFORMS J. Comput., 2015)

A Course on Advanced Software Tools for Operations Research and Analytics. - Iain Dunning; Vishal Gupta 004; Angela King; Jerry Kung; Miles Lubin; John Silberholz (INFORMS Trans. Educ., 2015)

Extended Formulations in Mixed-Integer Convex Programming. - Miles Lubin; Emre Yamangil; Russell Bent; Juan Pablo Vielma (IPCO, 2016)

Unit commitment with N-1 Security and wind uncertainty. - Kaarthik Sundar; Harsha Nagarajan; Miles Lubin; Line Roald; Sidhant Misra; Russell Bent; Daniel Bienstock (PSCC, 2016)

Reformulation versus cutting-planes for robust optimization. - Dimitris Bertsimas; Iain Dunning; Miles Lubin (Comput. Manag. Sci., 2016)

Forward-Mode Automatic Differentiation in Julia. - Jarrett Revels; Miles Lubin; Theodore Papamarkou (CoRR, 2016)

PowerModels.jl: An Open-Source Framework for Exploring Power Flow Formulations. - Carleton Coffrin; Russell Bent; Kaarthik Sundar; Yeesian Ng; Miles Lubin (CoRR, 2017)

Extended formulations in mixed integer conic quadratic programming. - Juan Pablo Vielma; Iain Dunning; Joey Huchette; Miles Lubin (Math. Program. Comput., 2017)

JuMP: A Modeling Language for Mathematical Optimization. - Iain Dunning; Joey Huchette; Miles Lubin (SIAM Rev., 2017)

Chance Constraints for Improving the Security of AC Optimal Power Flow. - Miles Lubin; Yury Dvorkin; Line Roald (CoRR, 2018)

Polyhedral approximation in mixed-integer convex optimization. - Miles Lubin; Emre Yamangil; Russell Bent; Juan Pablo Vielma (Math. Program., 2018)

On efficient Hessian computation using the edge pushing algorithm in Julia. - Cosmin G. Petra; Feng Qiang; Miles Lubin; Joey Huchette (Optim. Methods Softw., 2018)

REGAL: Transfer Learning For Fast Optimization of Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (CoRR, 2019)

Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (ICLR, 2020)

Outer approximation with conic certificates for mixed-integer convex problems. - Chris Coey; Miles Lubin; Juan Pablo Vielma (Math. Program. Comput., 2020)

Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient. - David L. Applegate; Mateo Díaz; Oliver Hinder; Haihao Lu; Miles Lubin; Brendan O'Donoghue; Warren Schudy (NeurIPS, 2021)

Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls. - Nick Doudchenko; Khashayar Khosravi; Jean Pouget-Abadie; Sébastien Lahaie; Miles Lubin; Vahab S. Mirrokni; Jann Spiess; Guido Imbens (NeurIPS, 2021)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Simon Bowly; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; et al. (NeurIPS (Competition and Demos), 2021)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; Andrea Lodi 001; et al. (CoRR, 2022)

JuMP 1.0. - Miles Lubin; Oscar Dowson; Joaquim Dias Garcia; Joey Huchette; Benoît Legat; Juan Pablo Vielma (CoRR, 2022)

MathOptInterface: A Data Structure for Mathematical Optimization Problems. - Benoît Legat; Oscar Dowson; Joaquim Dias Garcia; Miles Lubin (INFORMS J. Comput., 2022)

Mixed-Integer Convex Representability. - Miles Lubin; Juan Pablo Vielma; Ilias Zadik (Math. Oper. Res., 2022)

Faster first-order primal-dual methods for linear programming using restarts and sharpness. - David L. Applegate; Oliver Hinder; Haihao Lu; Miles Lubin (Math. Program., 2023)

JuMP 1.0: recent improvements to a modeling language for mathematical optimization. - Miles Lubin; Oscar Dowson; Joaquim Dias Garcia; Joey Huchette; Benoît Legat; Juan Pablo Vielma (Math. Program. Comput., 2023)

Shapes and recession cones in mixed-integer convex representability. - Ilias Zadik; Miles Lubin; Juan Pablo Vielma (Math. Program., 2024)

Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming. - David L. Applegate; Mateo Díaz; Haihao Lu; Miles Lubin (SIAM J. Optim., 2024)