OMLT: Optimization & Machine Learning Toolkit

4 February 2022

Papers citing "OMLT: Optimization & Machine Learning Toolkit"

21 / 21 papers shown

Title
Reinforcement learning with combinatorial actions for coupled restless bandits Lily Xu Bryan Wilder Elias B. Khalil Milind Tambe 67 1 0 01 Mar 2025
Training Neural ODEs Using Fully Discretized Simultaneous Optimization Mariia Shapovalova Calvin Tsay 29 2 0 24 Feb 2025
Formulations and scalability of neural network surrogates in nonlinear optimization problems Robert B. Parker Oscar Dowson Nicole LoGiudice Manuel Garcia Russell Bent 61 0 0 16 Dec 2024
Verifying message-passing neural networks via topology-based bounds tightening Christopher Hojny Shiqiang Zhang Juan S. Campos Ruth Misener AAML 39 6 0 21 Feb 2024
Physics-Informed Neural Networks with Hard Linear Equality Constraints Hao Chen Gonzalo E. Constante-Flores Canzhou Li PINN 13 9 0 11 Feb 2024
Generating Likely Counterfactuals Using Sum-Product Networks Jiri Nemecek Tomás Pevný Jakub Marecek TPM 65 0 0 25 Jan 2024
Optimization Over Trained Neural Networks: Taking a Relaxing Walk Jiatai Tong Junyang Cai Thiago Serra 60 6 0 07 Jan 2024
Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks Fabian Badilla Marcos Goycoolea Gonzalo Muñoz Thiago Serra 57 7 0 27 Dec 2023
PySCIPOpt-ML: Embedding Trained Machine Learning Models into Mixed-Integer Programs Mark Turner Antonia Chmiela Thorsten Koch Michael Winkler AI4CE 49 8 0 13 Dec 2023
Neur2RO: Neural Two-Stage Robust Optimization Franccois Hélénon J. Huber F. B. Amar Stéphane Doncieux 11 4 0 06 Oct 2023
Data-driven decision-focused surrogate modeling Rishabh Gupta Qi Zhang OffRL AI4CE 25 12 0 23 Aug 2023
Optimizing the switching operation in monoclonal antibody production: Economic MPC and reinforcement learning Sandra A. Obiri Song Bo B. T. Agyeman Benjamin Decardi-Nelson Jinfeng Liu 13 2 0 07 Aug 2023
A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch Shengren Hou Edgar Mauricio Salazar Duque Peter Palensky Pedro P. Vergara 13 4 0 26 Jul 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 91 32 0 29 Apr 2023
Model-based feature selection for neural networks: A mixed-integer programming approach Shudian Zhao Calvin Tsay Jan Kronqvist 19 5 0 20 Feb 2023
Physics Informed Piecewise Linear Neural Networks for Process Optimization Ece S. Koksal E. Aydın PINN 8 11 0 02 Feb 2023
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces Alexander Thebelt Calvin Tsay Robert M. Lee Nathan Sudermann-Merx David Walz B. Shafei Ruth Misener UQCV BDL 25 10 0 02 Jul 2022
Neur2SP: Neural Two-Stage Stochastic Programming Justin Dumouchelle R. Patel Elias Boutros Khalil Merve Bodur 49 26 0 20 May 2022
P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints Jan Kronqvist Ruth Misener Calvin Tsay 46 7 0 10 Feb 2022
Maximizing information from chemical engineering data sets: Applications to machine learning Alexander Thebelt Johannes Wiebe Jan Kronqvist Calvin Tsay Ruth Misener AI4CE 27 68 0 25 Jan 2022
Mixed-Integer Optimization with Constraint Learning Donato Maragno H. Wiberg Dimitris Bertsimas Ş. Birbil D. Hertog Adejuyigbe O. Fajemisin 51 50 0 04 Nov 2021