Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2001.09394
Cited By
v1
v2 (latest)
Lagrangian Duality for Constrained Deep Learning
26 January 2020
Ferdinando Fioretto
Pascal Van Hentenryck
Terrence W.K. Mak
Cuong Tran
Federico Baldo
M. Lombardi
PINN
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Lagrangian Duality for Constrained Deep Learning"
50 / 62 papers shown
A Dual Perspective on Decision-Focused Learning: Scalable Training via Dual-Guided Surrogates
Paula Rodriguez-Diaz
Kirk Bansak Elisabeth Paulson
OffRL
355
0
0
07 Nov 2025
Enforcing convex constraints in Graph Neural Networks
Ahmed Rashwan
Keith Briggs
Chris Budd
L. Kreusser
151
0
0
13 Oct 2025
Learning to Solve Optimization Problems Constrained with Partial Differential Equations
Yusuf Guven
Vincenzo Di Vito
Ferdinando Fioretto
AI4CE
145
1
0
29 Sep 2025
Robust Non-Linear Correlations via Polynomial Regression
Luca Giuliani
M. Lombardi
54
0
0
11 Sep 2025
Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers
Panagiotis D. Grontas
Antonio Terpin
Efe C. Balta
Raffaello DÁndrea
John Lygeros
250
8
0
14 Aug 2025
Learning Robust Satellite Attitude Dynamics with Physics-Informed Normalising Flow
Carlo Cena
Mauro Martini
Marcello Chiaberge
PINN
257
0
0
11 Aug 2025
Learning to Solve Constrained Bilevel Control Co-Design Problems
James Kotary
Himanshu Sharma
Ethan King
D. Vrabie
Ferdinando Fioretto
Ján Drgoňa
174
2
0
11 Jul 2025
Constrained Sliced Wasserstein Embedding
Navid Naderializadeh
Darian Salehi
Hengrong Du
Soheil Kolouri
287
6
0
02 Jun 2025
Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation
Jacob K Christopher
Michael Cardei
Jinhao Liang
Ferdinando Fioretto
DiffM
MedIm
283
7
0
01 Jun 2025
FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
Hoang T. Nguyen
Priya L. Donti
277
8
0
31 May 2025
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow
Michael Klamkin
Mathieu Tanneau
Pascal Van Hentenryck
209
10
0
28 May 2025
Constrained Machine Learning Through Hyperspherical Representation
Integration of AI and OR Techniques in Constraint Programming (CPAIOR), 2025
Gaetano Signorelli
Michele Lombardi
231
1
0
11 Apr 2025
Training-Free Constrained Generation With Stable Diffusion Models
Stefano Zampini
Jacob K Christopher
Luca Oneto
Davide Anguita
Ferdinando Fioretto
548
12
0
08 Feb 2025
Towards graph neural networks for provably solving convex optimization problems
Chendi Qian
Christopher Morris
383
3
0
04 Feb 2025
Learning To Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito
M. Mohammadian
K. Baker
Ferdinando Fioretto
AI4CE
215
3
0
02 Oct 2024
Physics-Informed Graph-Mesh Networks for PDEs: A hybrid approach for complex problems
Advances in Engineering Software (Adv. Eng. Softw.), 2024
M. Chenaud
Frédéric Magoulès
José Alves
AI4CE
PINN
242
4
0
25 Sep 2024
Learning Joint Models of Prediction and Optimization
European Conference on Artificial Intelligence (ECAI), 2024
James Kotary
Vincenzo Di Vito
Jacob Cristopher
Pascal Van Hentenryck
Ferdinando Fioretto
222
5
0
07 Sep 2024
A Catalog of Fairness-Aware Practices in Machine Learning Engineering
Gianmario Voria
Giulia Sellitto
Carmine Ferrara
Francesco Abate
A. Lucia
F. Ferrucci
Gemma Catolino
Fabio Palomba
FaML
403
5
0
29 Aug 2024
On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization
International Conference on Machine Learning (ICML), 2024
Motahareh Sohrabi
Juan Ramirez
Lucas Maes
Damien Scieur
Jose Gallego-Posada
318
7
0
07 Jun 2024
Physics-Informed Real NVP for Satellite Power System Fault Detection
Carlo Cena
Umberto Albertin
Mauro Martini
Silvia Bucci
Marcello Chiaberge
217
7
0
27 May 2024
Fairness-Accuracy Trade-Offs: A Causal Perspective
Drago Plečko
Elias Bareinboim
300
16
0
24 May 2024
Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming
Ethan King
James Kotary
Ferdinando Fioretto
Ján Drgoňa
307
8
0
01 Apr 2024
Near-Optimal Solutions of Constrained Learning Problems
International Conference on Learning Representations (ICLR), 2024
Juan Elenter
Luiz F. O. Chamon
Alejandro Ribeiro
223
9
0
18 Mar 2024
Learning Constrained Optimization with Deep Augmented Lagrangian Methods
James Kotary
Ferdinando Fioretto
212
16
0
06 Mar 2024
Geometry-Informed Neural Networks
Arturs Berzins
Andreas Radler
Eric Volkmann
Sebastian Sanokowski
Sepp Hochreiter
Johannes Brandstetter
GAN
AI4CE
607
8
0
21 Feb 2024
Disparate Impact on Group Accuracy of Linearization for Private Inference
International Conference on Machine Learning (ICML), 2024
Saswat Das
Marco Romanelli
Ferdinando Fioretto
FedML
281
4
0
06 Feb 2024
Multi-dimensional Fair Federated Learning
AAAI Conference on Artificial Intelligence (AAAI), 2023
Cong Su
Guoxian Yu
Jun Wang
Hui Li
Qingzhong Li
Han Yu
FedML
252
11
0
09 Dec 2023
On The Fairness Impacts of Hardware Selection in Machine Learning
Sree Harsha Nelaturu
Nishaanth Kanna Ravichandran
Cuong Tran
Sara Hooker
Ferdinando Fioretto
363
5
0
06 Dec 2023
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework
Mitchell Keegan
Mahdi Abolghasemi
247
2
0
06 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
249
4
0
22 Nov 2023
Achieving Constraints in Neural Networks: A Stochastic Augmented Lagrangian Approach
Diogo Mateus Lavado
Cláudia Soares
Alessandra Micheletti
221
3
0
25 Oct 2023
Self-supervised Equality Embedded Deep Lagrange Dual for Approximate Constrained Optimization
Minsoo Kim
Hongseok Kim
280
5
0
11 Jun 2023
Resilient Constrained Learning
Neural Information Processing Systems (NeurIPS), 2023
Ignacio Hounie
Alejandro Ribeiro
Luiz F. O. Chamon
393
17
0
04 Jun 2023
Generalized Disparate Impact for Configurable Fairness Solutions in ML
International Conference on Machine Learning (ICML), 2023
Luca Giuliani
Eleonora Misino
M. Lombardi
190
9
0
29 May 2023
On the Fairness Impacts of Private Ensembles Models
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Cuong Tran
Ferdinando Fioretto
248
7
0
19 May 2023
Learning with Explanation Constraints
Neural Information Processing Systems (NeurIPS), 2023
Rattana Pukdee
Dylan Sam
J. Zico Kolter
Maria-Florina Balcan
Pradeep Ravikumar
FAtt
393
10
0
25 Mar 2023
Do Machine Learning Models Learn Statistical Rules Inferred from Data?
International Conference on Machine Learning (ICML), 2023
Aaditya Naik
Yinjun Wu
Mayur Naik
Eric Wong
299
5
0
02 Mar 2023
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints
Conference on Learning for Dynamics & Control (L4DC), 2022
Kaustubh Sridhar
Souradeep Dutta
James Weimer
Insup Lee
456
8
0
02 Dec 2022
The intersection of machine learning with forecasting and optimisation: theory and applications
M. Abolghasemi
181
2
0
24 Nov 2022
Policy Learning for Nonlinear Model Predictive Control with Application to USVs
Rizhong Wang
Huiping Li
Bin Liang
Yang Shi
Deming Xu
348
46
0
18 Nov 2022
Automatic Data Augmentation via Invariance-Constrained Learning
International Conference on Machine Learning (ICML), 2022
Ignacio Hounie
Luiz F. O. Chamon
Alejandro Ribeiro
375
20
0
29 Sep 2022
Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints
Neural Information Processing Systems (NeurIPS), 2022
Jose Gallego-Posada
Juan Ramirez
Akram Erraqabi
Yoshua Bengio
Damien Scieur
416
28
0
08 Aug 2022
Pruning has a disparate impact on model accuracy
Neural Information Processing Systems (NeurIPS), 2022
Cuong Tran
Ferdinando Fioretto
Jung-Eun Kim
Rakshit Naidu
309
51
0
26 May 2022
Enhanced Physics-Informed Neural Networks with Augmented Lagrangian Relaxation Method (AL-PINNs)
Neurocomputing (Neurocomputing), 2022
Hwijae Son
S. Cho
H. Hwang
PINN
276
81
0
29 Apr 2022
Competitive Physics Informed Networks
International Conference on Learning Representations (ICLR), 2022
Qi Zeng
Yash Kothari
Spencer H. Bryngelson
F. Schafer
PINN
251
26
0
23 Apr 2022
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Cuong Tran
Keyu Zhu
Ferdinando Fioretto
Pascal Van Hentenryck
224
12
0
11 Apr 2022
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Ferdinando Fioretto
Cuong Tran
Pascal Van Hentenryck
Keyu Zhu
FaML
290
72
0
16 Feb 2022
A Lagrangian Duality Approach to Active Learning
Neural Information Processing Systems (NeurIPS), 2022
Juan Elenter
Navid Naderializadeh
Alejandro Ribeiro
442
30
0
08 Feb 2022
End-to-end Learning for Fair Ranking Systems
The Web Conference (WWW), 2021
James Kotary
Ferdinando Fioretto
Pascal Van Hentenryck
Ziwei Zhu
FaML
629
24
0
21 Nov 2021
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method
AAAI Conference on Artificial Intelligence (AAAI), 2021
James Kotary
Ferdinando Fioretto
Pascal Van Hentenryck
245
27
0
12 Oct 2021
1
2
Next
Page 1 of 2
