Papers citing 'Partition-based formulations for mixed-integer optimization of trained ReLU neural networks'

Title
Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees Daniel Ovalle Lorenz T. Biegler Ignacio E. Grossmann Carl D. Laird Mateo Dulce Rubio 182 0 0 04 Jun 2025
Global optimization of graph acquisition functions for neural architecture search Yilin Xie Shiqiang Zhang Jixiang Qing Ruth Misener Calvin Tsay 202 3 0 29 May 2025
Tightening convex relaxations of trained neural networks: a unified approach for convex and S-shaped activations Pablo Carrasco Gonzalo Muñoz 202 3 0 30 Oct 2024
SMLE: Safe Machine Learning via Embedded OverapproximationAAAI Conference on Artificial Intelligence (AAAI), 2024 Matteo Francobaldi Michele Lombardi AAML 97 1 0 30 Sep 2024
A constrained optimization approach to improve robustness of neural networks Shudian Zhao Jan Kronqvist AAML 188 0 0 18 Sep 2024
Certified Robustness to Data Poisoning in Gradient-Based Training Philip Sosnin Mark N. Müller Maximilian Baader Calvin Tsay Matthew Wicker AAML SILM 215 14 0 09 Jun 2024
Verifying message-passing neural networks via topology-based bounds tightening Christopher Hojny Shiqiang Zhang Juan S. Campos Ruth Misener AAML 257 12 0 21 Feb 2024
Physics-Informed Neural Networks with Hard Linear Equality ConstraintsComputers and Chemical Engineering (Comput. Chem. Eng.), 2024 Hao Chen Gonzalo E. Constante-Flores Canzhou Li PINN 119 34 0 11 Feb 2024
Feed-Forward Neural Networks as a Mixed-Integer Program Navid Aftabi Nima Moradi Fatemeh Mahroo 94 8 0 09 Feb 2024
Machine learning for industrial sensing and control: A survey and practical perspectiveControl Engineering Practice (Control Eng. Pract.), 2024 Nathan P. Lawrence S. Damarla Jong Woo Kim Aditya Tulsyan Faraz Amjad Kai Wang Benoît Chachuat Jong Min Lee Biao Huang R. Bhushan Gopaluni AI4CE 168 38 0 24 Jan 2024
Optimization Over Trained Neural Networks: Taking a Relaxing Walk Jiatai Tong Junyang Cai Thiago Serra 285 13 0 07 Jan 2024
Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks Fabian Badilla Marcos Goycoolea Gonzalo Muñoz Thiago Serra 246 7 0 27 Dec 2023
Mixed-Integer Optimisation of Graph Neural Networks for Computer-Aided Molecular DesignComputers and Chemical Engineering (Comput. Chem. Eng.), 2023 Tom McDonald Calvin Tsay Artur M. Schweidtmann Neil Yorke-Smith 227 20 0 02 Dec 2023
Evaluating robustness of support vector machines with the Lagrangian dual approach Yuting Liu Hong Gu Pan Qin AAML 193 5 0 05 Jun 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 512 43 0 29 Apr 2023
Certifiably-correct Control Policies for Safe Learning and Adaptation in Assistive Robotics K. Majd Geoffrey Clark Tanmay Khandait Siyu Zhou S. Sankaranarayanan Georgios Fainekos H. B. Amor 143 1 0 12 Mar 2023
Safe Robot Learning in Assistive Devices through Neural Network RepairConference on Robot Learning (CoRL), 2023 K. Majd Geoffrey Clark Tanmay Khandait Siyu Zhou S. Sankaranarayanan Georgios Fainekos H. B. Amor 155 1 0 08 Mar 2023
Model-based feature selection for neural networks: A mixed-integer programming approachLearning and Intelligent Optimization (LION), 2023 Shudian Zhao Calvin Tsay Jan Kronqvist 199 7 0 20 Feb 2023
Physics Informed Piecewise Linear Neural Networks for Process OptimizationComputers and Chemical Engineering (Comput. Chem. Eng.), 2023 Ece S. Koksal E. Aydın PINN 187 18 0 02 Feb 2023
Piecewise Linear Neural Networks and Deep LearningNature Reviews Methods Primers (NRMP), 2022 Qinghua Tao Li Li Xiaolin Huang Xiangming Xi Shuning Wang Johan A. K. Suykens 110 37 0 18 Jun 2022
Optimizing Objective Functions from Trained ReLU Neural Networks via Sampling Georgia Perakis Asterios Tsiourvas 182 14 0 27 May 2022
P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraintsMathematical programming (Math. Program.), 2022 Jan Kronqvist Ruth Misener Calvin Tsay 211 10 0 10 Feb 2022
OMLT: Optimization & Machine Learning ToolkitJournal of machine learning research (JMLR), 2022 Francesco Ceccon Jordan Jalving Joshua Haddad Alexander Thebelt Calvin Tsay C. Laird Ruth Misener 239 93 0 04 Feb 2022
Maximizing information from chemical engineering data sets: Applications to machine learning Alexander Thebelt Johannes Wiebe Jan Kronqvist Calvin Tsay Ruth Misener AI4CE 324 85 0 25 Jan 2022
Constraint Learning to Define Trust Regions in Predictive-Model Embedded Optimization Chenbo Shi Mohsen Emadikhiav Leonardo Lozano David Bergman 154 2 0 12 Jan 2022
Optimizing over an ensemble of neural networks Keliang Wang Leonardo Lozano C. Cardonha David Bergman UQCV 188 1 0 13 Dec 2021
Modeling Design and Control Problems Involving Neural Network SurrogatesComputational optimization and applications (COA), 2021 Dominic Yang Dali Wang S. Leyffer 132 16 0 20 Nov 2021
Lyapunov-stable neural-network control Hongkai Dai Benoit Landry Lujie Yang Marco Pavone Russ Tedrake 151 145 0 29 Sep 2021
Local Repair of Neural Networks Using Optimization K. Majd Siyu Zhou H. B. Amor Georgios Fainekos S. Sankaranarayanan 139 6 0 28 Sep 2021
Where the Action is: Let's make Reinforcement Learning for Stochastic Dynamic Vehicle Routing Problems work! Florentin D Hildebrandt Barrett Thomas M. Ulmer 82 8 0 28 Feb 2021
Optimal training of integer-valued neural networks with mixed integer programmingPLoS ONE (PLOS ONE), 2020 Tómas Thorbjarnarson Neil Yorke-Smith 302 9 0 08 Sep 2020