DC3: A learning method for optimization with hard constraints

25 April 2021

J. Zico Kolter

Papers citing "DC3: A learning method for optimization with hard constraints"

38 / 38 papers shown

Title
Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach Rares Cristian Pavithra Harsha Georgia Perakis Brian Quanz 12 0 0 16 May 2025
Towards graph neural networks for provably solving convex optimization problems Chendi Qian Christopher Morris 52 0 0 04 Feb 2025
Differentiable Projection-based Learn to Optimize in Wireless Network-Part I: Convex Constrained (Non-)Convex Programming Xiucheng Wang Xuan Zhao Nan Cheng 44 0 0 29 Jan 2025
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 163 3 0 14 Oct 2024
Generative Edge Detection with Stable Diffusion Caixia Zhou Yaping Huang Mochu Xiang Jiahui Ren Haibin Ling Jing Zhang 59 0 0 04 Oct 2024
Unconditional stability of a recurrent neural circuit implementing divisive normalization Shivang Rawat David J. Heeger Stefano Martiniani 29 0 0 27 Sep 2024
Self-Supervised Learning of Iterative Solvers for Constrained Optimization Lukas Luken Sergio Lucia 36 0 0 12 Sep 2024
Differentiable-Optimization Based Neural Policy for Occlusion-Aware Target Tracking Houman Masnavi Arun Kumar Singh Farrokh Janabi-Sharifi 54 0 0 20 Jun 2024
Dual Interior Point Optimization Learning Michael Klamkin Mathieu Tanneau Pascal Van Hentenryck 30 2 0 04 Feb 2024
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework Mitchell Keegan Mahdi Abolghasemi 59 0 0 06 Dec 2023
Energy-based Potential Games for Joint Motion Forecasting and Control Christopher P. Diehl Tobias Klosek Martin Krüger Nils Murzyn Timo Osterburg Torsten Bertram AI4CE 29 6 0 04 Dec 2023
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization James Kotary Vincenzo Di Vito Jacob K Christopher Pascal Van Hentenryck Ferdinando Fioretto 39 3 0 22 Nov 2023
OpenForest: A data catalogue for machine learning in forest monitoring Arthur Ouaknine T. Kattenborn Etienne Laliberté David Rolnick 53 6 0 01 Nov 2023
RAYEN: Imposition of Hard Convex Constraints on Neural Networks J. Tordesillas Jonathan P. How Marco Hutter 32 11 0 17 Jul 2023
End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch Wenbo Chen Mathieu Tanneau Pascal Van Hentenryck 34 30 0 23 Apr 2023
End-to-End Learning with Multiple Modalities for System-Optimised Renewables Nowcasting Rushil Vohra A. Rajaei J. Cremer 24 5 0 14 Apr 2023
Contingency Analyses with Warm Starter using Probabilistic Graphical Model Shimiao Li Amritanshu Pandey L. Pileggi AI4CE 34 2 0 10 Apr 2023
Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees Rahul Nellikkath Spyros Chatzivasileiadis 36 3 0 23 Mar 2023
Constrained Empirical Risk Minimization: Theory and Practice Eric Marcus Ray Sheombarsing J. Sonke Jonas Teuwen 15 1 0 09 Feb 2023
Compact Optimization Learning for AC Optimal Power Flow Seonho Park Wenbo Chen Terrence W.K. Mak Pascal Van Hentenryck 32 17 0 21 Jan 2023
Minimizing Worst-Case Violations of Neural Networks Rahul Nellikkath Spyros Chatzivasileiadis 38 3 0 21 Dec 2022
Evaluating Model-free Reinforcement Learning toward Safety-critical Tasks Linrui Zhang Qin Zhang Li Shen Bo Yuan Xueqian Wang Dacheng Tao OffRL 48 26 0 12 Dec 2022
Unsupervised Deep Learning for AC Optimal Power Flow via Lagrangian Duality Ke Chen Shourya Bose Yu Zhang 15 7 0 07 Dec 2022
The intersection of machine learning with forecasting and optimisation: theory and applications M. Abolghasemi 23 1 0 24 Nov 2022
Deep Equilibrium Approaches to Diffusion Models Ashwini Pokle Zhengyang Geng Zico Kolter DiffM 30 39 0 23 Oct 2022
Differentiable Constrained Imitation Learning for Robot Motion Planning and Control Christopher P. Diehl Janis Adamek Martin Krüger F. Hoffmann Torsten Bertram 16 4 0 21 Oct 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization Seonho Park Pascal Van Hentenryck 38 46 0 18 Aug 2022
Physics-Informed Learning of Aerosol Microphysics P. Harder D. Watson‐Parris P. Stier Dominik Strassel N. Gauger J. Keuper 19 20 0 24 Jul 2022
Learning differentiable solvers for systems with hard constraints Geoffrey Negiar Michael W. Mahoney Aditi S. Krishnapriyan 34 28 0 18 Jul 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Constraint-based graph network simulator Yulia Rubanova Alvaro Sanchez-Gonzalez Tobias Pfaff Peter W. Battaglia PINN AI4CE 32 28 0 16 Dec 2021
DNN-based Policies for Stochastic AC OPF Sarthak Gupta Sidhant Misra Deepjyoti Deka V. Kekatos 34 13 0 04 Dec 2021
Physics-Informed Neural Networks for AC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 34 88 0 06 Oct 2021
Learning to Solve the AC Optimal Power Flow via a Lagrangian Approach Ling Zhang Baosen Zhang 22 8 0 04 Oct 2021
Graph Neural Network-based Resource Allocation Strategies for Multi-Object Spectroscopy Tianshu Wang P. Melchior 18 7 0 27 Sep 2021
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 51 614 0 02 Sep 2021
Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 13 32 0 28 Jun 2021
First-order Methods Almost Always Avoid Saddle Points J. Lee Ioannis Panageas Georgios Piliouras Max Simchowitz Michael I. Jordan Benjamin Recht ODL 95 82 0 20 Oct 2017